Impact of capillary rise and recirculation on crop yields

This paper describes impact analyses of various soil water flow regimes on grass, maize 10 and potato yields in the Dutch delta, with a focus on upward soil water flows capillary rise and recirculation towards the rootzone. Flow regimes are characterised by soil composition and groundwater depth and derived from a national soil database. The intermittent occurrence of upward flow and its influence on crop growth are simulated with the combined SWAP-WOFOST model using various boundary conditions. Case studies and model 15 experiments are used to illustrate impact of upward flow on yield and crop growth. This impact is clearly present in situations with relatively shallow groundwater levels (85% of the Netherlands), where capillary rise is the main flow source; but also in free-draining situations the impact of upward flow is considerable. In the latter case recirculated percolation water is the flow source. To make this impact explicit we implemented a synthetic modelling option 20 that stops upward flow from reaching the root zone, without inhibiting percolation. Such a hypothetically moisture-stressed situation compared to a natural one in the presence of shallow groundwater shows mean yield reductions for grassland, maize and potatoes of respectively 25, 4 and 15 % or respectively about 3.2, 0.5 and 1.6 ton dry matter per ha. About half of the withheld water behind these yield effects comes from recirculated 25 percolation water as occurs in free drainage conditions and the other half comes from increased upward capillary rise. Soil water and crop growth modelling should consider both capillary rise from groundwater and recirculation of percolation water as this improves the accuracy of yield simulations. This also improves the accuracy of the simulated groundwater recharge: neglecting these processes causes overestimates of 17% for grassland and 46% 30 for potatoes, or 70 and 34 mm a, respectively. Impact of capillary rise and recirculation on crop yields Joop Kroes, Iwan Supit Jos Van Dam, Paul Van Walsum, Martin Mulder Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2017-223, 2017 Manuscript under review for journal Hydrol. Earth Syst. Sci. Discussion started: 20 April 2017 c © Author(s) 2017. CC-BY 3.0 License.

experiments are used to illustrate impact of upward flow on yield and crop growth. This impact is clearly present in situations with relatively shallow groundwater levels (85% of the Netherlands), where capillary rise is the main flow source; but also in free-draining situations the impact of upward flow is considerable. In the latter case recirculated percolation water is the flow source. To make this impact explicit we implemented a synthetic modelling option 20 that stops upward flow from reaching the root zone, without inhibiting percolation. Such a hypothetically moisture-stressed situation compared to a natural one in the presence of shallow groundwater shows mean yield reductions for grassland, maize and potatoes of respectively 25, 4 and 15 % or respectively about 3.2, 0.5 and 1.6 ton dry matter per ha.
About half of the withheld water behind these yield effects comes from recirculated 25 percolation water as occurs in free drainage conditions and the other half comes from increased upward capillary rise. Soil water and crop growth modelling should consider both capillary rise from groundwater and recirculation of percolation water as this improves the accuracy of yield simulations. This also improves the accuracy of the simulated groundwater recharge: neglecting these processes causes overestimates of 17% for grassland and 46%

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Crop growth strongly depends on soil moisture conditions. Climate variables determine these conditions through rain that penetrates directly into the root zone or comes available via lateral flow. The moisture distribution in the soil strongly depends on soil physical properties that determine vertical flow. Upward soil water flow becomes an especially vital supply term of a crop when the soil water potential gradient induced by the root-extraction 40 manages to bridge the distance to the capillary fringe, inducing increased capillary rise. In this paper we follow the definition of capillary rise, given by SSSA (2008), as the "phenomenon that occurs when small pores which reduce the water potential are in contact with free water". This implies that capillary rise as a source for upward flow to crop roots requires the presence of a groundwater table. In conditions without a groundwater table   45 there may also be a contribution of upward flow to crop roots through the process of recirculation. Recirculation is a known process discussed already by Feodoroff (Rijtema and Wassink, 1969), but has never been quantified. We quantified recirculation separately from capillary rise using model experiments.
The contribution of (intermittent) upward flow to the total water budget can be significant. For 50 example Kowalik (2006) mentions that during the grass growing season, in soils with the groundwater close to the soil surface (Aquepts) the capillary rise induced by root extraction varies between 60 and 150 mm per year. Babajimopoulos et al. (2007) found that under the specific field conditions about 3.6 mm/day of the water in the root zone originated from the shallow water table, which amounts to about 18% of the water transpired by a maize crop.
55 Fan et al. (2013) analysed the groundwater depth globally and concluded that shallow groundwater influences 22 to 32% of global land area, and that 7 to 17% of this area has a water table within or close to plant rooting depths, suggesting a widespread influence of groundwater on crops. This is especially the case in delta areas where high population densities occur and agriculture is the predominant land use.
60 Wu et al. (2015) showed that capillary rise plays a main role in supplying the vegetation throughout the season with water, hence a strong dependence of vegetation upon groundwater. Han et al. (2015) applied HYDRUS-1D with a simplified crop growth model and concluded for cotton in a north-western part of China that capillary rise from groundwater contributes almost to 23% of crop transpiration when the average groundwater 65 depth is 1.84 m. According to Geerts et al. (2008) the contribution from capillary rise to the quinoa [Chenopodium quinoa Willd.] production in the Irpani region (Peru), ranges from 8 to 25% of seasonal crop evapotranspiration (ETc) of quinoa, depending mostly on groundwater table depth and amount of rainfall during the rainy season. The contribution from a groundwater table located approximately 1.5 to 2 m deep may represent up to 30% of the 70 soybean [Glycine max (L.) Merr.] water requirements in sandy pampas (Videla Mensegue et al., 2015).
In 85% of the area in the Netherlands the average groundwater table is less than 2 meter below the soil surface in (De Vries, 2007), where root extraction can induce capillary rise 75 from groundwater. Wesseling and Feddes (2006) report that in summers with a high evapotranspiration demand, crops partially depend on water supply from soil profile storage and induced capillary rise. Van der Gaast et al. (2009), applying the method of Wesseling (1991), found for the Netherlands a maximum capillary flow of 2 mm/d to the root zone in loamy soils where the groundwater level is at 2.5 meter below the soil surface.

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Although the contribution of capillary rise to the total water budget can be significant, it is an often neglected part of the crop water demand in situations of shallow groundwater levels (Awan et al., 2014). The capillary properties of a soil strongly depend on soil type. Rijtema (1971) estimated that loamy soils have an almost 2 times higher capillary rise than sandy soils.

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Integrated approaches are needed to relate water availability to crop yield prognosis (Van der Ploeg and Teuling, 2013;Norman, 2013). The importance of capillary rise as supplier of water to crops has been shown by many researchers (e.g. Hooghoudt, 1937;Huo et al., 2012;Talebnejad, and Sepaskhah, 2015;Han et al., 2015); however we found only a few 90 studies that use an integrated modelling approach (Xu et al., 2013;Zipper et al. 2015) to quantify capillary rise for different hydrological conditions (including free drainage) using physically based approaches. In this study we explicitly consider the effect of crop type, soil type, weather year and drainage condition on capillary rise. Zipper et al. (2015) introduced the concept of groundwater yield subsidy as the increase in harvested yield (kg/ha -1 ) in the 95 presence of shallow groundwater compared to free drainage conditions. Following their line we introduce the concept of soil moisture yield subsidy as additional yield increase in free drainage conditions due to recirculation of percolated soil moisture.
The driving force for induced capillary rise and recirculation is the difference in soil water 100 potential, referred to as heads, at different soil depths. There are several models available that solve these head differences numerically. Ahuja et al. (2014) evaluated 11 models commonly applied for agricultural water management. Six of these models use simple 'bucket' approaches for water storage and have in some cases been extended with more or less empirical options for capillary rise. Five models have the ability to numerically solve We applied the integrated model SWAP-WOFOST (acronyms for Soil Water Atmosphere Plant -WOrld FOod Studies) to solve head differences and crop yield simulations. Kroes and Supit (2011) applied the same integrated model to quantify the impact of increased 110 groundwater salinity on drought and oxygen of grassland yields in the Netherlands. They recommended further analyses using different crops and different boundary conditions. We now apply this model with different boundary conditions using 45 years of observed weather and three different crops. For the lower boundary we use different hydrologic conditions that influence the vertical flow. For the soil system itself we use a wide range of soil physical 115 conditions. The importance of the soil system was already stated by several authors like Supit (2000). We build on their suggestions and apply the tools for different crops and boundary conditions. Before we applied the model to different boundary conditions we validated it at field scale.

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This paper quantifies the effects of (intermittent) upward flow on crop growth under different conditions of soil hydrology, soil type and weather. The effects are separately quantified in terms of flow source, namely capillary rise and recirculated percolation water. Therefore we introduced a synthetic model option and performed a numerical experiment. We studied forage maize, grassland and potatoes and we hypothesize that neglecting upward flow will 125 result in neglecting a considerable amount of soil moisture that is available for crop growth.  We applied the coupled SWAP and WOFOST modeling system, using a one day time step.
SWAP (Van Dam et al., 2008;Kroes et al., 2017) is a one-dimensional physically based transport model for water, heat and solute in the saturated and unsaturated zone, and includes modules for simulating irrigation practices. The first version of SWAP, called SWATRE, was developed by Feddes et al. (1978). SWAP simulates the unsaturated and 140 saturated water flow in the upper part of the soil system, using a numerical solution of the where:  is volumetric water content (cm 3 cm -3 ), t is time (d), K(h) is hydraulic conductivity (cm d -1 ), h is soil water pressure head (cm) and z is the vertical coordinate (cm), taken 145 positively upward, () a Sh is soil water extraction rate by plant roots (d -1 ), () d Sh is the extraction rate by drain discharge in the saturated zone (d -1 ) and () m Sh is the exchange rate with macro pores (d -1 ).
Root water extraction and lateral exchange with surface water are accounted for. In this 150 study we do not use the option to exchange water flow with macro pores.
The soil hydraulics are described by the Mualem-van Genuchten relations and the potential evapotranspiration is calculated with the Penman-Monteith equation (Allen et al., 1998). At the bottom boundary hydraulic heads, supplied by a separate regional hydrological model can be used to simulate interaction between bottom boundary fluxes and groundwater 155 levels. Drainage and infiltration through the lateral boundary account for the flow to surface water. The surface water system is simulated using a simplified, weir controlled, water balance. Note that the surface water system in its turn interacts with the groundwater system. In previous years, SWAP has been successfully used to study soil-wateratmosphere-plant relationships in many locations with various boundary conditions (e.g. 160 Feddes et al., 1988;Bastiaanssen et al., 2007). See Van Dam et al. (2008) for an overview.

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WOFOST is a crop growth simulation model, its principles are explained by Van Keulen and Wolf (1986). Van Diepen et al. (1989) presented the first WOFOST version. WOFOST is applied in many studies (e.g. Rötter, 1993;Van Ittersum et al., 2003;de Wit and Van Diepen, 2008;Supit et al., 2012;De Wit et al., 2012). Crop assimilation is calculated as function of solar radiation and temperature, using a 3 point Gaussian integration method 170 accounting for leaf angle distribution and extinction of direct and diffuse light. The assimilation is reduced when water or nutrient stress occurs. Subsequently, the maintenance respiration is subtracted and the remaining assimilates are partitioned over the plant organs (i.e. leaves, stems, roots and storage organs). For maize and potatoes the partitioning is development stage dependent. For perennial grass however, a constant 175 partitioning factor is assumed. By integrating the difference between growth and senescence rates over time, dry weights of various plant organs are established.
In SWAP-WOFOST, crop assimilation depends on the ambient CO 2 concentration as well (see: Kroes and Supit, 2011;Supit et al., 2012). To account for unknown residual stress caused by diseases, pests and/or weeds an additional assimilation reduction factor is 180 introduced. The rooting density decreases exponentially with depth. To withdraw water from deeper soil layers for crop uptake a form of compensatory root uptake is used in case the upper part of the soil is very dry (Jarvis, 2011). The increasing atmospheric CO 2 concentrations during relatively long historical simulation periods (>20 years) is accounted for.  Table 1. The soil texture ranges from sand to clay. The observations included parameters, such as groundwater levels, yields and in some cases soil moisture contents, soil pressure head and evapotranspiration. The weather data were collected from nearby weather stations or from onsite measurements. Observations for case studies 1 and 2 (DM-Grass and DM-Maize in Table 1) were available for a period of 22 years  195 from one field where grassland and maize was grown for respectively 7 and 15 years. We used the model calibrations carried out by Kroes et al. (2015) and Hack et al. (2016) and limited our calibration efforts to parameter values for drought and management (Table 1), focussing on validation of results. Planting and harvest dates were given. Oxygen stress was parameterised as described by Hack et al. (2016). Drought stress was parameterised 200 using the dry part of the reduction function proposed by Feddes et al. (1978). Drought stress is absent when the soil pressure head h exceeds the critical value of h3. Drought stress increases linearly between h3 and at h4 (wilting point). The critical pressure head h3 differs between lower and higher potential transpiration (respectively h3l and h3h) rates.
For all cases a so-called management factor was used to close the gap between observed 205 and actual yield. The input crop parameters for maize only differed with respect to the management factor which ranges from 0.85-0.95. The management factors are relatively high because the case study locations have good management. It is very likely that we miss some processes even though our modelling approach is mechanistic, because it is still relatively simple. Some processes like pests and diseases are not included and may play a 210 role in the field; the calibration was done on experimental farms where the impact from diseases and pests is minimal.
For potatoes the input crop parameters were kept the same for all 3 cases (Tabel 1).
Maximum rooting depth for grassland, maize and potatoes were respectively 40, 100 and 50 cm.

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Soil water conditions were different for all locations and boundary conditions varied, depending on local situation and available data (Table 1). In most cases a Cauchy bottom boundary condition was applied using a hydraulic head based on piezometer observations from the Dutch Geological Survey (https://www.dinoloket.nl/). Observed groundwater levels were used as lower boundary condition for Borgerswold (crop: potato). In 2 cases a lateral boundary condition was applied with drainage to a surface water system (Table 1). The simulation results were analysed using an R-package (Bigiarini, 2013) and the statistics are presented in Table 2.

Soil crop experiment to analyse the role of capillary rise
To analyse the impact of soil type on upward soil water flow we modelled soil-crop experiments using 72 soils derived from a national soil data base (Wösten et al., 2013a). This synthetic option will be distributed with the latest model release.
The upward flux across the bottom of the root zone can either stem from capillary rise or from percolation water that is recirculated (q recirc and q caprise , see Figure 2  The crop parameters were kept the same as for the case studies, with a few exceptions: i) for grassland an average management factor of 0.9 was used, ii) timing of grass-mowing was done when a dry matter threshold of 4200 kg.ha -1 DM (Dry Matter) was exceeded, iii) for maize and potatoes the harvesting dates were respectively set to 25-Oct and 15-Oct.

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The 3 crops and 3 lower boundary conditions resulted in 9 combinations. Each combination was simulated with 72 soils for a period of 45 years  with meteorological data from the station De Bilt (KNMI, 2016). In a subsequent analysis we grouped the results of these 72 soils to 5 main soil groups clay, loam, peat, peat-moor and sand ( Figure 3) to be 280 able to analyse the impact at grouped soil types.

Case studies for validation
The first 2 case studies are from one location (De Marke) where a grassland-maize rotation was practised. The results show that the hydrological conditions ( Figure 4 and Table 2) were simulated accurately for those years for which observed data were available (1991)(1992)(1993)(1994)(1995).  Table 2).
For the other 2 maize case studies (C-Maize and D-Maize) groundwater levels and soil moisture are well simulated ( Table 2). The simulated maize yields (Table 2) are less acceptable for case C-Maize as is indicated by a zero or negative Nash-Sutcliffe efficiency (NS) which suggests that the observed mean is a better predictor than the model. In 1976, a very dry year, the soil hydrology dynamics and the resulting yield were well captured. The yield of case study D-Maize has a small bias of about 300 kg.ha -1 DM between observed 300 and simulated.
The simulated hydrological conditions for the 3 fields of the potato-cases R-Potato and V-Potato show a good fit with the observed ( Table 2). The simulated yields (Table 2)  Even though some yields are not accurate enough to satisfy statistical criteria for good 310 model performance, we think that the dynamics of soil hydrology and crop yield are acceptably captured. With more field information and calibration a better result could be achieved but we think that current tuning of SWAP-WOFOST for the 3 crops allows an application at a larger scale with various hydrological boundary conditions.

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Before the analysis at a larger scale we simulated the impact of upward flow for the case studies. We carried out additional simulations without upward flow towards the root zone, using the specially programmed synthetic model option. Results of these 3 cases are given in Table 3 for the situation with and without upward flow. This table shows that suppressing upward flow lowers yields by 5, 2 and 22% respectively for grassland, maize and potato .

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The groundwater recharge was reduced with respectively 3, 5 and 94% (Table 3). In a next step we carried out a larger scale experiment to quantify this impact for different soil crop and climate conditions.  Table 4). In free-draining soils the variation of capillary rise ranges from about 10 mm in wet and cold to 150 mm in dry and warm years with a high evaporative demand (Figures 6, upper part). In general capillary rise is highest in loamy soils where soil physical conditions are optimal. Especially in the presence of a groundwater level 340 differences in capillary rise between soils are relatively small compared to differences among years and within one grouped soil type (Figure 7, lower part).  Table 4). Note that the high value for perennial grassland is also caused by a much longer growing season. The percolation is highest for grassland for the same reasons (Table   4). These high values are largely due to the precipitation excess during winter in the Netherlands.

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Upward seepage across the bottom boundary does not occur in the free-drainage conditions ( Figure 2 a and b). Leaching is highest (Table 4) in the synthetic free-drainage condition without capillary rise (Figure 2 a). Note that the values in Table 4   greater depth leaching does not occur because excess water due to precipitation and/or upward seepage is discharged via drainage systems. The average condition we used has no leaching but seepage of 227, 155 and 291 mm.year -1 for grassland, maize and potatoes.
As can be expected, the synthetic condition without upward flow and without groundwater 365 (Figure 2 a), has the lowest simulated mean yields for all crops (Table 4). The highest mean yields are simulated when average groundwater situations including capillary rise are considered (Table 4, Ave). The relative mean yield increase is lowest for maize and highest for grassland (Table 5) which is probably caused by the difference in rooting depth.

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The simulation results with 3 different lower boundary conditions (Figure 2 conditions a, b and c) are also compared by subtraction. The subtraction enables a quantification of the contribution of the 2 different sources of upward flow: groundwater and recirculating percolation water.
The elimination of recirculating percolation water to the root zone in free drainage conditions 375 (synthetic condition a compared to b, Figure 2) reduces grassland, maize and potato yields with respectively 13, 1 and 8 % ( Table 5). The higher yields are caused by upward flow using recirculating percolation water as source.
A comparison between situations with free drainage (condition b, Figure 2) with average groundwater levels (condition c, Figure 2) shows a similar yield reduction: respectively. 13, 3 380 and 8 %. The higher yields are caused by upward flow using groundwater as source.
When one compares situations with free-drainage conditions without capillary rise (synthetic condition a, Figure 2) with average groundwater levels (condition c) yield-reductions of grassland, maize and potatoes are respectively 25, 4 and 15 % (Table 5) or respectively about 3.2, 0.5 and 1.6 ton.ha -1 dry matter (Table 4). These yield differences quantify the 385 contribution of the sum of the two different sources of upward flow: groundwater and recirculating percolation water.
The impact of upward flow on groundwater recharge is highest for potatoes and lowest for maize. For grassland, maize and potatoes differences between downward flux across the bottom of the rootzone (q percolation in Figure 2) of 3 hydrological conditions were calculated of 390 respectively 17, -6 and 46% (q percolation in Table 5) or 64, -3 and 34 mm (q percolation in Table 4).
Low recharge values for maize are caused by deeper rooting systems which reduce these differences because groundwater levels are closer to the bottom of the root zone. For potatoes this difference in yield can reach values of more than 4 ton.ha -1 dry matter in stress conditions (Table 6).

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The results are presented in more detail in the Supplementary Materials.

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The case studies and soil-crop experiments in this paper demonstrate the combined interaction of upward flow and groundwater on crop yields. This impact is clearly present in situations where a groundwater level is present (85% of NL) but also in free-draining situations the impact of upward flow is considerable. According to our simulation results, grassland, maize and potatoes yields increase with respectively 15, 1 and 8% in free 405 drainage conditions when upward flow is included (Table 5). This increase is mainly caused by internal recirculation, i.e. a part of the downward flux past the root zone is redirected upward to the root zone as a result of gradient driven flow. When upward flow also has groundwater as a source simulated yields increases by another 16, 3 and 9% respectively. This increase is supported by a stronger capillary rise due to proximity to the groundwater.

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Comparing the simple simulations (no upward flow, no groundwater influence) to those with an average groundwater level and capillary rise shows yield increases of 25, 4 and 15%.
About half of these yield increases are caused by internal recirculation as occurs in free drainage conditions and the other half is caused by an increased upward capillary flow from the groundwater.

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Many crop models consider the soil system as a reservoir with only percolation and no upward flow (e.g. tipping bucket approach). Such models do not account for soil moisture redistribution within and below the root zone. As our simulations show, this kind of models underestimate crop yield and overestimate groundwater recharge, and implicitly 420 overestimate drought stress. The irrigation demand may be overestimated as well. The high percolation may also result in overestimation of groundwater recharge (leaching). Groundwater depth is important, because it determines the distance that the capillary flux has to bridge to reach the root zone and should be accounted for in crop modelling.

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Our analysis shows that soil properties and soil profile layering are important because differences in soil hydraulic properties influence vertical water flow. High upward flow values are found in loamy soils as is expected (Table 6, max row), but if water stress is high and upward flow is low the influence of soil type decreases and low upward flow values were found for loamy soils (Table 6, min row). Comparing the minimum yield values it shows that 430 there is a large difference between these soil types in free-drainage conditions with and without upward flow. This means that the storage capacity of loamy soils is larger than the one of sandy soils as can be expected. The yield variation between soil types in water stress conditions is large and illustrates the need for a proper soil schematization especially in stress full hydrological conditions. An adequate soil schematization is relevant for all models 435 but especially for those that use a bucket approach (FD nc ). As the influence of recirculation (FD rc ) increases, the yield variation becomes less and the influence of soil type decreases.
In situations without water stress the soil type is less important. In conditions where groundwater and capillary rise occurs (Ave) yield variation is hardly influenced by soil type.
Modelling concepts should consider dynamic interactions between soil water and crop 440 growth. Crop models in general should consider recirculation of soil water and, especially in low lying regions like deltas, groundwater dynamics should be considered as well.
Precipitation, soil texture and water table depth jointly affected the amount of groundwater recharge and time-lag between water input and groundwater recharge (Ma et al., 2015). We 445 quantified some of these issues, but several items remain, such as the impact of rooting depth on crop yield and transpiration. Also soil and water management practises like ploughing and irrigation, are not considered. Furthermore the rooting pattern needs a more detailed analysis; we applied an exponential decrease of root density and compensation of root uptake according to Jarvis (2011) but the macroscopic root water uptake concept is still simple and requires a more detailed analyses (Dos Santos et al. 2017). Another item we neglected is the preferential flow of water by the occurrence of non-capillary sized macropores (Bouma, 1961, Feddes, 1988, which is relevant in especially clay soils.
Hysteresis of the water retention function is also not considered. An additional analysis of these issues is recommended, especially the impact of different rooting patterns on capillary 455 rise should be addressed.
The impact of soil type on yield increases when environmental conditions become dryer; situations without groundwater and without upward flow have less yield and higher yield variation than situations where groundwater influences capillary rise (For detailed 460 information on results see the Supplementary Materials).

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We quantified the impact of upward flow on crop yields of grassland, maize and potatoes in layered soils. We compared situations with average groundwater levels with free-drainage conditions with and without upward flow. The largest impact of upward flow on crop yields was found when one compares situations with average groundwater levels with free drainage conditions without upward flow. From these differences one may conclude that 470 neglecting upward flow has a large impact on simulated yields and water balance calculations especially in regions where shallow groundwater occurs. The comparison shows long term average yield-reductions of grassland, maize and potatoes of respectively 25, 4 and 15 % (Table 5) or respectively 3.2, 0.5 and 1.6 ton Dry Matter per ha (Table 4).
Reduction of the percolation flux can be considerable; for grassland and potatoes the 475 reduction is 17 and 46% (Table 5) or 70 and 34 mm (Table 4).
About half of the yield increases is caused by internal recirculation as occurs in freedrainage conditions and the other half is caused by an increased upward capillary flow from groundwater. Improved modelling should consider upward flow of soil water which will result in improved estimates of crop yield and percolation.

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We think that the quantification of upward flow on yield is a novelty, especially with respect to the interaction between recirculation and crop growth. Studies about the relation between soil hydrology and crop growth should quantify this upward flow because neglecting this flow and its impact implies neglecting yield changes which may have a large economic value in the Dutch Delta and in other deltas in general. Another aspect which cannot be found in the 485 referenced studies is the lack of a quantification of the impact of capillary rise and recirculation on crop yields. Correct quantification of the water fluxes contributes to the understanding of crop production and will help the institutions in charge of yield forecasting.

Acknowledgement
Part of the case studies has been used before (Hack et al., 2016). This project is related to the project WaterVision Agriculture (www.waterwijzer.nl) which is financed by a large group We also thank three anonymous reviewers for their constructive and valuable comments on earlier versions of this paper.