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Hydrological modelling is the same as developing and encoding a hydrological theory. A hydrological model is not a tool but a hypothesis. The whole discussion about the inadequacy of hydrological models we have witnessed of late, is related to the wrong concept of what a model is. Good models don't exist. Instead of looking for the "best" model, we should aim at developing better models. The process of modelling should be top-down, learning from the data while at the same time connection should be established with underlying physical theory (bottom-up). As a result of heterogeneity occurring at all scales in hydrology, there always remains a need for calibration of models. This implies that we need tailor-made and site-specific models. Only flexible models are fit for this modelling process, as opposed to most of the established software or "one-size-fits-all" models. The process of modelling requires imagination, inspiration, creativity, ingenuity, experience and skill. These are qualities that belong to the field of art. Hydrology is an art as much as it is science and engineering

In this paper we extend the validity of the classical linear solution for tidal hydrodynamics including the effects of width and depth convergence. Reworking such a solution in the light of externally defined, dimensionless parameters we are able to provide simple relationships to predict the most relevant features of the tidal wave at the estuary mouth (velocity amplitude, phase lag, wavelength, and damping) and to reproduce the main dynamics of tidal wave propagation along finite and infinite length channels. We also highlight the need for an accurate treatment of the linearized bed shear stress by exploiting an iterative procedure, and we show the improvement that can be reached by subdividing the entire estuary in shorter reaches. Different versions of the analytical solution are compared with numerical results, highlighting the strengths and weaknesses of the linear model.

It is widely recognized that food consumption patterns significantly impact water requirements. The aim of this paper is to quantify how food consumption patterns influence water requirements in China. The findings show that per capita water requirement for food (CWRF) has increased from 255 m3 cap-1y−1 in 1961 to 860 m3 cap-1 y−1 in 2003, largely due to an increase in the consumption of animal products in recent decades. Although steadily increasing, the CWRF of China is still much lower than that of many developed countries. The total water requirement for food (TWRF) has been determined as 1127 km3 y-1 in 2003. Three scenarios are proposed to project future TWRF, representing low, medium, and high levels of modernization (S1, S2, and S3, respectively). Analysis of these three scenarios indicates that TWRF will likely continue to increase in the next three decades. An additional amount of water ranging between 407 and 515 km3 y-1 will be required in 2030 compared to the TWRF in 2003. This will undoubtedly put high pressure on China's already scarce water resources. We conclude that the effect of the food consumption patterns on China's water resources is substantial both in the recent past and in the near future. China will need to strengthen "green water" management and to take advantage of "virtual water" import to meet the additional TWRF

The upper Ewaso Ng’iro basin, which starts from the central highlands of Kenya and stretches northwards transcending different climatic zones, has experienced decreasing river flows for the last two decades. The Naro Moru sub-basin is used to demonstrate the looming water crisis in this water scarce river basin. The objective of the study was to show the extent of dry seasons’ irrigation water abstractions on river flows, and to assess the hydrological impact of flood storage on temporal water distribution and irrigation water management. Decreasing river flows are attributed to over-abstraction mainly for irrigating horticultural crops. The number of abstractors has increased four times over a period of 10 years. The amount of water abstracted has also increased by 64% over the last 5 years. Moreover, the proportion of unauthorized abstractions has been increasing over the years, currently at about 80% and 95% during high and low flows respectively. This has resulted in alarming conflicts among various water users. The situation is aggravated by low irrigation efficiency (25–40%) and inadequate flood storage facilities. The paper analyzes over 40 years’ observed river flow data and 5-year interval water abstraction monitoring records for 15 years. It assesses whether flood storage and management, can reduce dry seasons’ irrigation water abstractions without significantly reducing river flows to affect the sustenance of natural ecosystems downstream. The results demonstrate that flood storage and management can reduce water abstraction and increase river flows during the dry seasons, without significantly reducing high flows to affect the downstream water users. However, socio-economic, hydrological and environmental implications should be considered if a sustainable river basin water resources management strategy is to be developed and implemented. The case study of Naro Moru sub-basin is representative of the situation in the other sub-basins, and hence can be taken as a pilot basin for developing an integrated water resources management strategy that will foster socio-economic development with minimal negative hydrological impacts in the water scarce upper Ewaso Ng’iro river basin.

A priori determined model structures are common in catchment rainfall-runoff modeling. While this has resulted in many ready-to-use modeling tools, there are several shortcomings of a one-size-fits-all model structure. The uniqueness of catchments with respect to their hydrological behavior and the need to adapt model complexity to data availability challenge this status quo. We present a flexible approach to model development where the model structure is adapted progressively based on catchment characteristics and the data described by the experimentalist. We demonstrate this approach with the Maimai catchment in New Zealand, a location with a large availability of data, including stream discharge, groundwater levels, and stream isotope measurements. Different types of data are introduced progressively, and the architecture of the model is adjusted in a stepwise fashion to better describe the processes suggested by the new data sources. The revised models are developed in a way to strike a balance between model complexity and data availability, by keeping models as simple as possible, but complex enough to explain the dynamics of the data. Our work suggests that (1) discharge data provides information on the dynamics of storage (represented by the “free” water in the reservoirs) subject to pressure wave propagation generated by rainfall into the catchment, (2) groundwater data provides information on thresholds and on the contribution of different portions of the catchment to stream discharge, and (3) isotope data provides information on particle transport and mixing of the rainfall with the storage present in the catchment. Moreover, while groundwater data appear to be correlated with discharge data, and only a marginal improvement could be obtained adding this information to the model development process, isotope data appear to provide an orthogonal view on catchment behavior. This result contributes to understanding the value of data for modeling, which may serve as a guidance in the process of gauging ungauged catchments.

Lack of data is one of the main limitations for hydrological modeling. However, it is often used as a justification for over simplifying, poorly performing models. If we want to enhance our understanding of hydrological systems, it is important to fully exploit the information contained in the available data, and to learn from model deficiencies. In this paper, we propose a methodology where we systematically update the model structure, progressively incorporating new hypotheses of catchment behavior. We apply this methodology to the Alzette river basin in Luxembourg, showing how stepwise model improvement helps to identify the behavior of this catchment. We show that the most significant improvement of the evolving model structure is associated to the characterization of antecedent wetness. This is improved accounting for interception, which affects vertical storage distribution, and accounting for rainfall spatial heterogeneity, which influences storage variations in the horizontal dimension. Overall, our results suggested that, due to the damping effect of the basin, the description of fast catchment response benefits more from spatially distributed information than that of slow catchment response.

This paper presents a simple analytical equation for monthly interception on the basis of the combination of a daily threshold model with the probability distribution of daily rainfall. In this paper, interception has a wider definition than merely canopy interception. It is the part of the rainfall that evaporates after it has been stored on the wetted surface, which includes the canopy, the understory, the bottom vegetation, the litter layer, the soil, and the hard surface. Interception is defined as the process of evaporation from intercepted rainfall. It is shown that this process has a typical timescale of 1 day. Monthly interception models can be improved by taking the statistical characteristics of daily rainfall into account. These characteristics appear to be less variable in space than the rainfall itself. With the statistical characteristics of daily rainfall obtained at a few locations where reliable records are available (for example, airports) monthly models can be improved and applied to larger areas (20–200 km). The equation can be regionalized, making use of the Markov property of daily rainfall. The equation obtained for monthly interception is similar to Budyko's curve.

Smallholder rainfed farming systems generally realise sub-optimal crop yields which are largely attributed to dry spell occurrences during crop growth stages. However, through the introduction of appropriate farming practices, it is possible to substantially increase yield levels even with little and highly variable rainfall. The presented results follow research conducted in the Makanya catchment in northern Tanzania where gross rainfall amounts to less than 400 mm/season which is insufficient to support staple food crops (e.g. maize). The yields from farming system innovations (SIs), which are basically alternative cultivation techniques, are compared against traditional farming practices. The SIs tested in this research are runoff harvesting used in combination with in-field trenches and soil bunds (fanya juus). These SIs aim to reduce soil and nutrient loss from the field and, more importantly, promote in-field infiltration and water retention. Water balance components have been observed in order to study water partitioning processes for the "with" and "without" SI scenarios. Based on rainfall, soil evaporation, transpiration, runoff and soil moisture measurements, a water balance model has been developed to simulate soil moisture variations over the growing season. Simulation results show that, during the field trials, the average productive transpiration flow ranged between 1.1–1.4 mm d−1 in the trial plots compared to 0.7–1.0 mm d−1 under traditional tillage practice. Productive transpiration processes accounted for 23–29% while losses to deep percolation accounted for 33–48% of the available water. The field system has been successfully modelled using the spreadsheet-based water balance 1-D model. Conclusions from the research are that the SIs that were tested are effective in enhancing soil moisture retention at field scale and that diversions allow crop growth moisture conditions to be attained with early rains. From the partitioning analysis, it is also concluded that there is more scope for efficient utilisation of the diverted runoff water if storage structures could be installed to minimise runoff and deep percolation and, hence, regulate water flow to the root zone when required

A conceptual hydrological model structure contains several parameters that have to be estimated through matching observed and modeled watershed behavior in a calibration process. The requirement that a model simulation matches different aspects of system response at the same time has led the calibration problem toward a multiobjective approach. In this work we compare two multiobjective calibration approaches, each of which represents a different calibration philosophy. The first calibration approach is based on the concept of Pareto optimality and consists of calibrating all parameters with respect to a common set of objectives in one calibration stage. This approach results in a set of Pareto‐optimal solutions representing the trade‐offs between the selected calibration objectives. The second is a stepped calibration approach (SCA), which implies a stepwise calibration of sets of parameters that are associated with specific aspects of the system response. This approach replicates the steps followed by a hydrologist in manual calibration and develops a single solution. The comparison is performed considering the same set of objectives for the two approaches and two model structures of a different level of complexity. The difference in the two approaches, their reciprocal utility, and the practical implications involved in their application are analyzed and discussed using the Hesperange catchment case, an experimental basin in the Alzette River basin in Luxembourg. We show that the two approaches are not necessarily conflicting but can be complementary. The first approach provides useful information about the deficiencies of a model structure and therefore helps the model development, while the second attempts at determining a solution that is consistent with the data available. We also show that with increasing model complexity it becomes possible to reproduce the observations more accurately. As a result, the solutions for the different calibration objectives become less distinguishable from each other, indicating that calibration results become less dependent on the objective functions used when the model is a better representation of reality and has a higher potential to reproduce the observations.

Observations in estuaries indicate that an amplified tidal wave moves considerably faster than is indicated by the classical equation for wave propagation. Similarly, the celerity of propagation is lower if the tidal wave is damped. This phenomenon is clearly observed in the Schelde estuary (located in the Netherlands and Belgium) and in the Incomati estuary in Mozambique. In the Incomati, the tidal wave is damped throughout, whereas in the Schelde the tidal range increases from the mouth until the city of Antwerp, after which it decreases until Gent. This paper derives a new analytical expression for the celerity of the tidal wave that takes into account the effect of tidal damping, as an expansion of the classical equation for tidal wave propagation. In the new equation the phase lag between high water and high water slack plays a crucial role. It is one of the main parameters determining tidal wave propagation in alluvial estuaries. The equation is successfully applied to observations in the Schelde and the Incomati.