Journal of Hydrology 401 (2011) 53–64

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Journal of Hydrology

journal homepage: www.elsevier .com/ locate / jhydrol

An evaluation of the application of treated sewage effluentsin Las Tablas de Daimiel National Park, Central Spain

Vicente Navarro ⇑, Beatriz García, David Sánchez, Laura AsensioGeoenvironmental Group, Civil Engineering Department, University of Castilla-La Mancha, Avda. Camilo José Cela s/n, 13071 Ciudad Real, Spain

a r t i c l e i n f o

Article history:Received 22 June 2010Received in revised form 16 December 2010Accepted 5 February 2011Available online 4 March 2011

This manuscript was handled by L. Charlet,Editor-in-Chief, with the assistance of PeterWolfgang Swarzenski, Associate Editor

Keywords:InfiltrationWater budgetInundationWetland

0022-1694/$ - see front matter � 2011 Elsevier B.V. Adoi:10.1016/j.jhydrol.2011.02.008

⇑ Corresponding author. Tel.: +34 926 295 453; faxE-mail addresses: Vicente.Navarro@uclm.es (V. Nav

(B. García), David.Sanchez@uclm.es (D. Sánchez), Lausio).

s u m m a r y

At the present time there is not enough information available to develop a quantitative model on howinundation takes place in the 1490 ha area of Tablas de Daimiel National Park (Central Spain) locatedupstream of Morenillo Dam. Given that it is the most important area in the Park from an ecological stand-point, this is a major concern, as it has not been possible to assess the potential effectiveness of the inter-ventions geared towards improving its current state. As a result, it is not feasible to simulate thehydrologic response to the application of treated sewage effluents, an initiative recently implementedby the Public Administration responsible for water management in the Guadiana River Basin, wherethe Park is located. To help solve this problem, a simplified model of the hydrologic behaviour of the sys-tem has been developed focusing on the characterisation of the main trends of the inundation process.Field data from 12 drying processes were used to identify the model parameters. Later, the evolutionof the system was examined after the application of treated sewage effluents, assuming the hypothesisof a dry climate. The results show that the 10 Mm3 of available effluents is sufficient to improve from2 ha to 60 ha the inundation condition of the areas considered to be high-priority. This therefore demon-strates that, from a hydrologic point of view, it is highly advisable to use treated sewage effluents.

� 2011 Elsevier B.V. All rights reserved.

1. Introduction

Tablas de Daimiel National Park (TDNP) is a floodplain wetlandwhich covers 1928 ha, located in the Upper Guadiana Basin(14,000 km2) over the West Mancha aquifer (5500 km2), in CentralSpain (Fig. 1a and b). Originally the wetland was the result of theoverflowing of the rivers Gigüela and Guadiana and the upwellingof waters from the aquifer. Additionally, 14 watermill weirscontributed to change from riverine to lacustrine conditions(Álvarez-Cobelas and Cirujano, 2007). TDNP is the most outstand-ing element of the wetland system known as ‘‘Mancha Húmeda’’(25,000 ha), declared a Biosphere Reserve in 1980 by UnitedNations Educational, Scientific and Cultural Organization(UNESCO). The West Mancha aquifer has been subject to intensivepumpage since the late 1970s. This has caused the phreatic level todecrease, as has been reported by a number of different authors(see, for example, Bromley et al., 2001; Conan et al., 2003;Custodio, 2002; Fornes et al., 2000; Llamas, 1988). As a result,the wetlands have been cut off from the regional aquifer, produc-ing major environmental damage. This has had a serious impact

ll rights reserved.

: +34 926 295 391.arro), Beatriz.Garcia@uclm.esra.Asensio@uclm.es (L. Asen-

on TDNP (Cirujano et al., 1996; Álvarez-Cobelas et al., 2001). Inthe past, a number of different measures were taken in an attemptto mitigate these repercussions, such as the construction of PuenteNavarro Dam (in 1985) and Morenillo Dam (in 1988) (Fig. 1c). Thelatter dam was built under the Tablas de Daimiel Hydric Regener-ation Plan of 1987, to improve the management of the watersupplied by the aqueduct Tagus-Segura (key structure of theTagus-Segura diversion). This water inflow was the main watersupply considered into the Regeneration Plan, but it was not theonly one. Several contingency wells were constructed to supplywater to the main ‘‘lagunas’’ (see Florín et al., 1993) (in Daimielthey are called ‘‘tablazos’’) which make up TDNP (Fig. 1d).Although water has been transferred from the Tagus River on anumber of different occasions since 1989, and pumpage from someof the contingency wells has been carried out on a relatively regu-lar basis, the situation of TDNP has gradually worsened. The Con-federación Hidrográfica del Guadiana (the Public Administrationresponsible for water management in the West Mancha aquifer)has recently considered the possibility of applying treated sewageeffluents (TSE) to improve the inundation condition. The effluentswill be properly treated at sewage plants to ensure optimum qual-ity when they reach the Park. It is beyond the scope of this paper toexamine how the treatment process itself is carried out and howoptimum quality is defined. Our aim here is to assess the feasibilityof this project from a hydrologic point of view. To do this, the

10 Km

N

Fuente El Fresno

Villarrubia de los Ojos

Daimiel

Guadiana River

Azuer RiverManzanares

Alcázar de San Juan

Las Tablas de Daimiel National Park

Special protection zone

0 5 km

N

Herencia

Malagón

Záncara River

Arenas de San Juan

Villarta de San Juan

Campo de Criptana

Membrilla

(a)

(b)

Fig. 1. (a) Situation of the Upper Guadiana Basin (black line), West Mancha aquifer (grey line), and La Mancha Húmeda Wetlands (grey areas). (b) Villages considered in thestudy. (c) Detailed plan view of the TDNP. Limnimeter 1 corresponds to Ojillo de Cañada Mendoza, 2 to Quinto de la Torre, 3 to Isleta de La Fuente, 4 to Tablazo and 5 toCasablanca. (d) Digital aerial photograph of Las Tablas de Daimiel National Park.

54 V. Navarro et al. / Journal of Hydrology 401 (2011) 53–64

Fig. 1 (continued)

V. Navarro et al. / Journal of Hydrology 401 (2011) 53–64 55

inundation pattern of TDNP must be simulated. Therefore, the firstobjective of this paper is to define a model of the TDNP hydrologicbehaviour.

2. Site inundation: description model

The Morenillo Dam separates the TDNP in two different areasfrom a hydrologic point of view. Whilst the zone of TDNP locateddownstream of Morenillo Dam (Las Cañas, see Fig. 1c) behaves like

a dam-reservoir single basin, the zone upstream of the dam (whichis specifically named ‘‘Las Tablas’’, Fig. 1c) has a more complexhydrologic behaviour. The field data obtained by the TDNP Techni-cal Staff (TDNP-TS) for floods caused by the arrival of water fromthe diversion of the Tagus-Segura through the Gigüela River high-lights the existence of a process of ‘‘activation’’ of a mixture ofsmall pools largely controlled by the small natural weirs formedby the vegetation.

In Las Tablas, ‘‘El Masegar’’ (a sawgrass meadow) is found,where the largest population of sawgrass (masiega, in Spanish) is

Fig. 2. Evolution of the inundated area with elevation. The water source is assumedto be at point P1 in Fig. 1c.

56 V. Navarro et al. / Journal of Hydrology 401 (2011) 53–64

currently concentrated (Cirujano and Álvarez-Cobelas, 2009, per-sonal communication; Álvarez-Cobelas et al., 2008). Given the spe-cial interest of this species for the Park, this is the mostenvironmentally valuable area. Hence, the inflow of TSE will be fo-cused on El Masegar. However, it is also of interest to inundate inthe old bed of the Guadiana River near the Molemocho mill (Fig.1c). It will serve to reduce the risk of combustion of the peat depos-its located in the old bed of the Guadiana River. Also, it will ensureponded conditions near the Molemocho mill, a building of utmostinterest from a cultural heritage point of view. Therefore, both

Fig. 3. Functional units (FU) considered in the

areas should be inundated, and despite its complex structure, thewhole inundation behaviour of Las Tablas should be analysed.

To do so, it is important to take into account that Las Tablasmorphology experiences relevant changes along the time. Thesechanges are not only due to the variability of the vegetation weirs,but also to the structural changes of the peat deposits of theGuadiana and Gigüela riverbeds (see Bradley, 2002, for a descrip-tion of changes of this kind). Even if it were possible to accuratelycharacterise this microtopography, it would be difficult to predictits evolution. So, it was deemed to be not affordable to obtain suchlevel of inundation detail. Although there exist different ‘‘smallinundation units’’, its characterisation was disregarded. The scaleof the approximation was enlarged, and effort was directed atcharacterising the main trends of the inundation pattern.

On the basis of the experience of the TDNP-TS, when water ar-rives by way of the Gigüela River, the first effect is the inundationof the ‘‘Central Zone’’, comprising roughly 100 ha, where El Mase-gar is located. After the inundation of El Masegar, the waterreaches the zone consisting of both the old bed of the GuadianaRiver and the final stretch of the Gigüela River (Fig. 1c), with anarea of around 151 ha (‘‘Guadiana–Gigüela Zone’’). At the start ofthe inundation of the Gigüela–Guadiana connection, the inunda-tion of the ‘‘Final Zone’’ is also initiated. This zone covers the areabetween the two previous zones (which connects through the flatchannels surrounding Pan Island, Fig. 1c), as well as the high partsof the ‘‘Central Zone’’.

The topographic data verify the existence of these three basicunits. To illustrate this, a digital elevation model recently devel-oped (spring 2007) by the TDNP-TS was used to draw up Fig. 2.It represents the evolution of the inundated area assuming that it

simplified hydrologic model of Las Tablas.

V. Navarro et al. / Journal of Hydrology 401 (2011) 53–64 57

has a water source situated at the lowest point at Molemocho mill,point P1 of Fig. 1c. The large discontinuity between z = 606.18 mand z = 606.19 m indicates the elevation at which theGuadiana–Gigüela Zone comes into contact with the Central Zoneand Final Zone, whereby some 100 ha of the centre are added tothe 151 ha of the Guadiana–Gigüela. At this height, there is alsoan increase in the speed at which the inundated area expands withthe elevation, mainly due to the flat morphology of the Final Zone.

Fig. 2 shows three lesser discontinuities when the elevation isequal to 606.00, 605.41 and 605.23 m, when the water floods onlythe Guadiana–Gigüela Zone (elevation less than 606.18 m). Thismay be attributed to the existence of four ‘‘sub-basins’’, althoughbetween sub-basins 2 and 3 hardly any morphometric discontinu-ity exists (at 605.41 m, discontinuity is barely noticeable).

Therefore, the scheme of the hydrologic behaviour of Las Tablasillustrated in Fig. 3 was adopted. Six functional units (FUs) wereconsidered. The first four pertain to the four sub-basins of theGuadiana–Gigüela Zone. The fifth is associated with the CentralZone, and the sixth is linked to the Final Zone.

Accordingly with the scale of approximation assumed, the char-acterisation of the spatial distribution of the inundation insideeach unit was disregarded. Only the ratio of inundated area was in-tended to be modelled by using a dynamic water budget (DWB)procedure. The use of water budgets has been thoroughly used inthe planning and management of wetlands, considering both quan-titative and environmental issues (see, among others, Brush et al.,2004; Dalton et al., 2004; Healy et al., 2007). Water budgets pro-vide a rational framework to identify the processes by means ofwhich water moves through the system, an essential point forthe calculation of nutrients, energy and chemical budgets (Lottand Hunt, 2001). The dynamic use of this method, although notso widely applied, has, however, been solidly validated. This canbe corroborated in the works by Lindley et al. (1995), Waltonet al. (1996), Saxton and Willey (2006), and Gasca and Ross(2009), for example. By applying the DWB, the inundated surfaceand volume are updated, thus resulting in a kind of ‘‘film’’ of theinundation process. However, if the process is not varied very grad-ually, major errors could occur, since hydrostatic conditions are as-sumed to exist in the DWB. To proceed correctly, the Navier–Stokesequations should be solved using shallow-waters flow models thatinclude ‘‘sink terms’’ associated with infiltration and evaporation.Nonetheless, flash flood processes are not usual in Las Tablas,

Fig. 4. Inundation data of the lim

and moreover are not the processes that this paper is dealing with.Rather, quasi-hydrostatic inundations are considered. For this rea-son DWB was used as the first simulation strategy. The next sec-tion describes its application.

3. Materials and methods

In all the systems analysed, the dynamic water budget equationwas computed:

dVdt¼ QIðtÞ � QOðtÞ þ RðtÞ þ ðpðtÞ � eðtÞ � irðtÞÞ � AðtÞ ð1Þ

where V (L3) is the inundated volume, QI (L3/T) is the inflow thatreaches the system, QO (L3/T) is the outflow, R (L3/T) is the lateralrun-on, p (L/T) is precipitation, e (L/T) the evapotranspiration, ir isthe infiltration rate (L/T), and A (L2) is the inundated area, relatedto V through the hypsometric curve. This ordinary differential equa-tion defines an initial value problem, which may be transformedinto a simple algebraic equation by using a derivative approxima-tion scheme (Finite Differences), and applying certain initial condi-tions to V and A. If a scheme based on the day to day discretisationwas used, the Euler method and the fourth order Runge Kutta meth-od (Press et al., 2002) were found to produce practically identicalresults in Las Tablas. Hence, Eq. (1) was approached in the followingway:

Viþ1 ¼ Vi þ ðQI � QOþ RÞi þ ðp� e� irÞi � Ai ð2Þ

where subscript ‘‘i’’ indicates the value of the variable on the ithday.

In the analyses conducted, the values of QI and QO were data.When field data (see Fig. 4) was used to calibrate the model, theonly series used were those in which both QI and QO were null.On the other hand, when making predictions for the future QOwere considered practically null in the emergency situations asso-ciated with the application of TSE, and QI was assumed to be equalto the TSE that were expected. An 18-year prediction time periodwas adopted bearing in mind that September 2027 is the deadlinefor achieving the objectives of the EU Water Framework Directive2000/60. The treated sewage effluent inflow was estimated usingdata taken from the Confederación Hidrográfica del Guadiana, aswell as from data on water consumption, the production of waste-water and population growth provided by the Instituto Nacional de

nimeters identified in Fig. 1c.

58 V. Navarro et al. / Journal of Hydrology 401 (2011) 53–64

Estadística (Public Administration responsible for the managementof statistical data in Spain). The resulting predictions are shown inFig. 5a–c and Table 1. TSE distribution by municipalities is given inTable 2. It will not be possible to apply all the effluents to the sameplace. In accordance with the results from the hydraulic studies(the program EPA SWMM 5.0; EPA, 2005 was used), in order totransport water by gravity flow pipe, it is advisable to considerthree different pipes, each one with a different discharge point inthe Park. The water from the towns located on the ‘‘Gigüela line’’(Campo de Criptana, Alcázar de San Juan, Herencia, Villarta deSan Juan, Arenas de San Juan and Villarrubia de los Ojos; 57.1% ofthe total effluent discharge) will be applied to FU 5, favouringthe inundation of the Masegar. The water from the towns of the‘‘Azuer line’’ (Membrilla-Manzanares and Daimiel; 40.4% of the to-

(a)

(b)

Fig. 5. (a) Prediction of the total treated sewage effluent inflow, applied to FU 1–2–3,distribution of the TSE.

tal effluent discharge) will be directed to FU 1. Finally, the 2.5% ofthe total corresponding to Fuente el Fresno will be applied to FU 4.

Both the average daily temperature T and p were data too. Thehistorical values were taken from the records (see weather stationin Fig. 1c), and a dry climate prediction for the future was assumed.Precipitation and temperature data from the hydrologic year1979–1980 to 1996–1997 were used. The average rainfall duringthis 18-year period corresponds to the 35th percentile of the aver-age rainfall of all the 18-year series that can be retrieved from 1961(first year in which daily information was available) to 2007. Thisway, a dry climate hypothesis was considered. Moreover, thesedata were modified to linearly decrease the mean precipitationby 10 mm, and linearly increase the mean temperature by 2 �C,during the 18-year simulation. The data roughness (standard

FU 4 and FU 5. (b) Precipitation and evaporation series (daily data). (c) Monthly

(c)

Fig. 5 (continued)

Table 1Annual volume of TSE.

Year V (Mm3) Year V (Mm3)

2010 10.58 2019 11.452011 10.67 2020 11.552012 10.76 2021 11.662013 10.86 2022 11.772014 10.95 2023 11.872015 11.05 2024 11.982016 11.15 2025 12.092017 11.25 2026 12.21

Table 2Percent distribution by populations of TSE.

Daimiel 19.4%Manzanares + Membrilla 21.0%Villarrubia 13.1%Alcázar de San Juan + Criptana 37.5%Herencia 4.7%Fuente el Fresno 2.5%Villarta de San Juan 1.0%Arenas de San Juan 0.8%

V. Navarro et al. / Journal of Hydrology 401 (2011) 53–64 59

deviation of the series) was not changed. So, the potential effect ofclimate change was introduced in a simplified manner (Moreno,2005). This type of climate simulation is, of course, an approxima-tion (see, for example, the paper published recently by Candelaet al. (2009) on how to obtain climate forecasting to evaluate thegroundwater consequences). However, in view of the uncertaintyassociated with the other variables involved in the simulations,the methodology was considered to be a good approximation forconsidering the potential effect of a dry series in the model.

R is calculated from p by means of the curve number method(NRCS, 2003). Since it was difficult to define the antecedent mois-ture condition, the possibility of using the approach proposed byYoung and Carleton (2006) was considered. Finally, however, ithas been decided to use the classic formulation based on the5-day antecedent rainfall, taking into consideration the rainfallrange determined by Mitchell et al. (1993). Although the run-onin Las Tablas is minor as compared to the other terms of the waterbudget, it should not be overlooked to consistently introduceheavy rainfall episodes into the simulation of the system. Whenrun-on is produced, it generally occurs on the right-hand marginof the Gigüela River, towards FUs 4 and 5.

Water loss by evapotranspiration was defined as (Cesanelli andGuarracino, 2009):

e ¼ KS � KC � ETO ð3Þ

where ETO is the reference evapotranspiration, KS describes the ef-fect of soil water stress, and KC is a crop coefficient. The referenceevapotranspiration was estimated from data of a class A evaporim-eter located in the weather station in Fig. 1c. The water stress coef-ficient varies from 0 (dry soil) to 1 (wet condition). In the dryingprocesses analysed in this paper, KS was assumed to be practicallyequal to 1. The value of KC was supposed to be variable accordingto the inundated area, as can be derived from the experimental dataof transpiration measured during 1997 and 1998 by Sánchez-Carrillo et al. (2004) for different crops, percentage of macrophytecover, open water/macrophyte cover ratio, and evaporation rate.On the basis of these data, it was inferred that KC has a value of 1for open water conditions, and 1.2 when the macrophyte cover pre-vails over open water conditions. These values are similar to thoseput forth by Allen et al. (1998) for the Food and Agriculture Admin-istration (FAO) of the United Nations. Hence, they were the valuesfinally used in the computations.

Once QI, QO, R, p and e have been defined, the behaviour of thesystem depends mainly on the value of ir. Hence, a plausible char-acterisation of its value is needed. However this type of informa-tion is not currently available. There are only two previousattempts to estimate ir. In an excellent, but largely overlooked,technical report, Ruano (1996) estimated a value of 5 mm/day inLas Cañas, and values of 15 mm/day, 6.5 mm/day and 24–33 mm/day were estimated in the Guadiana River near Molemocho mill,in the Tablazo de las Águilas, and in the Pasarelas area, respectively(see Fig. 1c). These reference values are based in short data series.Therefore, its scope is limited. Castaño (2003) and Castaño-Castañoet al. (2008) identified by using a local search algorithm a value of10 mm/day for the Park as a whole. Besides that the identificationmodel is not the most appropriate identification approach, theassumption that the inundation pattern of Las Tablas was equalto a dam reservoir is also debatable. According to the diagram ofthe model presented in Fig. 3, ir may, in principle, have a consider-ably distinct structure for each FU. In fact, its potential spatial var-iability inside each FU should also be considered.

If, as is commonly the case in areas of low topography, the infil-tration flow is assumed to be fundamentally vertical (see, forexample, Scanlon et al., 2002), the infiltration q (L/T) in a genericprofile ‘‘P’’ (see Fig. 6) may be expressed as:

Table 3Mean value of the effective hydraulic conductivity and infiltration rate identified indifferent areas of Las Tablas.

Parameter Area Value (mm/day) Source

Average ir Las Cañas 5 Ruano (1996)Average ir Guadiana, Molemocho 15 Ruano (1996)Average ir Tablazo de las Águilas 6.5 Ruano (1996)Average ir Pasarelas 24–33 Ruano (1996)Average ir Whole Park 10 Castaño (2003)KM1–4 FU 4 9 This workKM2–4 FU 4 21 This workKM1–123 FUs 1, 2 and 3 9 This workKM2–123 FUs 1, 2 and 3 8.5 This workKM1–1234 FUs 1 to 4 10 This workKM2–1234 FUs 1 to 4 11 This workKM1-TOT FUs 1 to 5 15 This workKM2-TOT FUs 1 to 5 13 This workKM1–5 FU 5 9 This workKM2–5 FU 5 21 This work

Fig. 6. Geometric variables considered in Eq. (4).

60 V. Navarro et al. / Journal of Hydrology 401 (2011) 53–64

qP ¼ KPð1þ ðZ � zPÞ=LPÞ ð4Þ

where KP (L/T) is the effective hydraulic conductivity (understood inthe sense of Vigiak et al., 2006; equivalent to the hydraulic conduc-tivity of the wetted zone of Bouwer, 1986) associated with profile P,LP (L) is the profile thickness from the surface to the groundwaterlevel; Z (L) is the elevation of the water level in the basin wherethe profile is located; and zP (L) is the surface elevation of the topof the profile (greater than zMIN (L), lower topographic elevationof the basin, and less than Z). Similar to what is common practicein other studies on wetlands or infiltration ponds (Lindley et al.,1995; Merritt and Konikow, 2000; Saxton and Willey, 2006), hereit was assumed that the effective hydraulic conductivity in the soilprofiles under Las Tablas had a steady value which was roughly thesame throughout the process analysed. This allows for the formula-tion of the average infiltration rate associated with Z as follows:

irðZÞ ¼ 1AðZÞ

Z AðZÞ

0qPdA ¼ 1

AðZÞ

Z AðZÞ

0KP 1þ Z � zP

LP

� �dA ð5Þ

where given the low topography, the wetted area is assumed to bepractically equal to the inundated area A. Despite its formal interest,practical difficulties are encountered in the application of this equa-tion since the distribution of the hydraulic conductivity must beknown. Even if a thorough hydrological field investigation were tobe conducted, the existence of undetected preferential infiltrationpaths will invalidate the averaging procedure and the field investi-gation effort (Brooks, 2005). Due to a number of different circum-stances such as the difficulties encountered in trying to locatethese preferential paths, along with the possibility that their loca-tion may change over time (as happens with microtopography),the lack of information available on bore logs, and the spatial vari-ability of the substrate soil verified by TDNP-TS, it was deemed bestto change the scale of analysis. Taking into account the scale used inEq. (1) to calculate the water mass balance, and the scale used to de-fine the inundation process, it was decided to work directly with theFUs as a support (in the sense the term is used by Pachepsky et al.,2006) for hydraulic conductivity. Thus, instead of working with theeffective hydraulic conductivity linked to each profile, its mean va-lue KM (L/T) associated with a certain elevation Z of the water level,was used. Eq. (5) was formulated as follows:

irðZÞ ¼ KMðZÞ �1

AðZÞ

Z Z

zMIN

1þ Z � zLðzÞ

� �dAðzÞ

� �¼ KMðZÞ � i Z; ZGWð Þ

ð6Þ

where i(Z) (dimensionless) is the mean value of the hydraulic gradi-ent, which depends on the geometry and groundwater level ZGW (L)(see Fig. 6).

By forgoing the possibility of obtaining the ir from the upscalingof q, not only did this mean giving up the possibility of obtaining aprediction of the ir values through the hierarchical consideration ofthe physical processes associated with the infiltration, it also

entailed the loss of a valuable tool to estimate the way in whichthe effective hydraulic conductivity varies in relation to the eleva-tion of the water level. It is not easy to define the way in which thisvariation would take place. On the one hand, it would be reason-able to expect KM to go from having a low value KM1 when, withlow inundated areas, the sediments from the bottom of the basinhave a considerable effect, to higher values as the water depth in-creases and the relative importance of the sediment width dimin-ishes. On the other hand, the low-elevation zones may coincidewith those having a higher interaction with the aquifer, whichmeans that they may have associated preferential flow pathswhich make KM1 higher. Therefore, a linear model between KM1

and KM2 (high inundated area) was adopted as a working hypoth-esis, without making any impositions as to which of these twovalues should be higher. The variation of the parameters KM1 andKM2 between functional units is a means by which the model intro-duces the variability of infiltration in Las Tablas.

4. Infiltration parameters

The ir linear model was applied to analyse limnimetric datafrom Quinto de la Torre when Z was less than 606.00 m (see Figs.1c and 4). Drying series from 2000, 2001, 2003 and 2004 were usedas calibration data (which is shown in Fig. 4). A systematic globalsearch by means of a grid-search algorithm (Neumaier, 2004)was used for identification. Values of KM1–4 (KM1 in FU 4) andKM2–4 from 0.1 to 50 mm/day were considered. This ‘‘search space’’was discretised by using a Cartesian grid with a spacing of0.05 mm/day. 996,004 pairs of parameters KM1–4–KM2–4 were ob-tained, and the drying processes of the years 2000, 2001, 2003and 2004 were simulated by means of a DWB procedure for eachone of the ir law defined by these pairs. The root mean square errorfunction (RMSE) was used to compare model and calibration data.The minimum was located at values of 9 mm/day for KM1–4 and21 mm/day for KM2–4 (see Table 3).

This global identification not only avoided potential problemswith local minima, it also provided a simple way to obtain Fig. 7(a representation of a part of the 996,004 RMSE values), in whichthe quality of the identification becomes evident when the topog-raphy of the error is represented. This figure, as well as the highlysatisfactory adjustment obtained when the field data used to cali-brate the identification were reproduced (1996 and 1999, Fig. 8),gives confidence to the model, indicating that the hypothesis of lin-ear variation of KM is a feasible model.

Unfortunately, it was not possible to carry out a similar task inFU 5, where El Masegar is located, because there are no available

K M2-

4 (m

m/d

ay)

KM 1-4 (mm/day)

Fig. 7. Variation of the Root Mean Square Error (RMSE, in ha) around the optimumvalues of the parameters that define the ir in FU 4.

V. Navarro et al. / Journal of Hydrology 401 (2011) 53–64 61

data on this FU separately. The limnimeter closest to FU 5 is inTablazo (see Fig. 1c), situated at the point of contact betweenFUs 5 and 6. Hence, limnimetric data of the infiltration in FU 5are only available when the water level is above 606.19 m, i.e.,when the rest of the FUs are also inundated. This is why it is noteasy to segregate the information related only to FU 5. Although di-rect identification is not possible, the available data do, however,contribute valuable information about the variation ranges of KM

in FU 5.

0

5

10

15

20

25

30

35

40

45

50

01/0

8/19

96

11/0

8/19

96

21/0

8/19

96

31/0

8/19

96

10/0

9/19

96

20/0

9/19

96

A (h

a)

0

5

10

15

20

25

30

35

40

45

50

10/0

7/19

99

20/0

7/19

99

30/0

7/19

99

09/0

8/19

99

19/0

8/19

99

A (h

a)

(a)

(b)

Fig. 8. Calibration: time series of inundation data

This information was first obtained by analysing the data fromQuinto de la Torre when Z was between 606.18 m and 606.00 m.Hence, once again, by assuming a linear model, it was possible toidentify the variation of ‘‘KM–1234’’, the value of KM when FUs 1, 2,3 and 4 are inundated. It is important to note that both in this caseand in the identification of KM1–4 and KM2–4, as well as in theanalyses described below, although the information from Quintode la Torre was used, a previous verification was made to checkthe consistency with the data taken from the other limnimeters(Fig. 4). Using drying periods from 1996 and 2003, the values ofKM1–1234 and KM2–1234 from Table 3 were identified. The qualityof the identification was similar to what was shown for KM1–4

and KM2–4 in Fig. 7.The next step was to analyse the drying process which in 1997

affected all the FUs when the water level went from Z = 606.91 mto Z = 606.19 m. By applying the same hypotheses and proceduresas in the two cases described above, the values of KM1-TOT andKM2-TOT in Table 3 were identified.

When the water level is between Z = 606.18 m and Z = 606.19 m,the full inundation of FUs 1, 2, 3, 4 and 5 is achieved, but withpractically no inundation in the zones between them. Therefore,the mean value of the effective hydraulic conductivity can be calcu-lated as the weighted average of KM2–1234 (equal to 11 mm/d, inun-dated area of 151.9 ha) and KM2–5 (unknown value, inundated areaof 99.6 ha). This weighted value is assumed to be close to 15 mm/d, i.e., a KM1-TOT. It is deduced that KM2–5 will be equal to 21 mm/d,a value identical to KM2–4.

To estimate the value of KM1–5, given the morphology of FUs 3and 5, as well as the nature of their sediments (Sánchez-Carrilloet al., 2001b), it was judged reasonable to assume a certain degreeof analogy between the hydrogeologic functioning of FU 5 and the

0.00

0.05

0.10

0.15

0.20

0.25

0.30

30/0

9/19

96

10/1

0/19

96

20/1

0/19

96

30/1

0/19

96

09/1

1/19

96

19/1

1/19

96A-MOD

A-EXP

V-MOD

V-EXP

0.00

0.05

0.10

0.15

0.20

0.25

0.30

29/0

8/19

99

08/0

9/19

99

18/0

9/19

99

28/0

9/19

99

V (M

m3 )

V (M

m3 )

A-MOD

A-EXP

V-MOD

V-EXP

(symbols) and model results (lines) in FU 4.

62 V. Navarro et al. / Journal of Hydrology 401 (2011) 53–64

group formed by FUs 1–2–3 once its function as a flood plain hasbecome more important than its role as a stream bed. This isthought to happen above Z = 605.45 m. It is therefore of interestto analyse the drying data from Ojillo de Cañada Mendoza whenZ ranged from 605.99 m to 605.59 m.

The data from 2000, 2001 and 2003 were used to identify thevalues of KM2–123 and KM1–123 in Table 3. The latter value is equalto KM1–4 and practically equal to KM1–1234. Therefore KM1–5 9 =mm/d was used.

The characterisation of KM in FU 4, and in the group of FUs 1–2–3, not only served to gather more criteria to estimate KM1–5 andKM2–5. It also allowed for the evaluation of the potential effective-ness of the application of the TSE of the Azuer line to FU1, and theTSE of Fuente el Fresno to FU4.

Fig. 9. Estimation of the evolution of the inundated area in FU 5.

5. Evaluation of the TSE application

As pointed out by Cirujano et al. (1996), the basic priority atTDNP is to inundate the Park. So, once a plausible variation rangehas been defined for KM in FU 5, i.e., once the variables that affectthe hydrologic behaviour of the system have been marked, whatmust be evaluated is whether or not the available TSE is able toinundate it. In order to do this, it has been decided to simulatethe long-term effect of TSEs, even though one must be aware thata simulation of this type has serious drawbacks.

The first and perhaps most fundamental question is that it mustalways bear in mind that Las Tablas, as a life system, is a dynami-cally changing system. In fact, in keeping with the results reportedby Sánchez-Carrillo et al. (2001a), its rate of change (as far assedimentation is concerned) is higher than in other wetlands.Although it is true that by forgoing the execution of a detailedsimulation of the spatial distribution of the inundation, the depen-dency of the model was substantially reduced with regard to thechanging microtopography, even the simplified model used willbe affected by the time evolution of the system in long-term sim-ulations. Most likely the scale used to simulate the infiltration willcontribute a certain amount of time stability to the model. How-ever, the data used to estimate the infiltration are associated witha time window of 8 years, which may be too short. Therefore, evenif it is assumed that the infiltration model is still valid, it must beremembered that, associated with the parameters that have beenidentified, there is a certain degree of uncertainty that cannot beoverlooked.

The long-term simulation also entails another difficulty. Giventhat the response of the system depends on the inundated area,and the inundated area depends, in turn, on the water inflow, ifonly the contribution of TSE is considered and not the dischargesfrom the Gigüela River, the simulations will not be accurate. More-over, by trying to estimate the streamflow of the Gigüela, a prob-lem of an even larger scope may be faced, since it would entailthe simulation precision of the integrated hydrologic–hydrogeo-logical behaviour of the Upper Guadiana Basin. This is no easy task,given that the amount of information available in the basin isscarce. Thus, for example, although the group of researchers whoare the authors of this paper have an integrated hydrologic–hydro-geological model of the Upper Guadiana Basin, its precision (cellsof 2.5 � 2.5 km, monthly computational time-steps) is not appro-priate for use in the research proposed here. Therefore, it wasnot used to simulate the discharges of the Gigüela River. The sim-ulation was carried out based only on the contribution of TSE, onthe lateral run-on, and on the assumption that the outflow associ-ated with TSE was null.

For all of the above reasons, the results did not have ‘‘true phy-sic’’ significance since they do not indicate the inundation thatwould take place at a given moment in time. They should be

considered to be a sensitivity analysis of a system’s ability torespond, contributing information to generate better speculation(Allen et al., 2003) on the application of TSE.

Fig. 9 shows the estimation of the response of FU 5 assumingthe mean effective hydraulic conductivity characterised by the val-ues or KM1–5 and KM2–5 recorded in Table 3. As indicated, there isenough TSE available to generate a very significant improvementin the inundation conditions, since full inundation is achieved dur-ing a high percentage of winters. Under these conditions, the areaof water covers roughly 100 ha. This area has been given the name‘‘net inundated area’’ (NIA), and includes the area of open waterand the inundated emergent macrophyte cover. Owing to the exis-tence of small elevations, this area is not continuous. It is possibleto define an exterior boundary that surrounds the inundated zones.The area inside this line is the area that will be seen as inundated,including the NIA and the islands within the wetland that providewetland habitat. This area is called the ‘‘equivalent inundated area’’(EIA). In FU 5 when the net area is 100 ha, the equivalent inundatedarea is equal to roughly 192 ha. It never shows values of less than20 ha of EIA in summer and after the first 3 years it has been con-sistently above 30 ha.

During several episodes, the full inundation of FU 5 (elevation606.18 m) is reached. In this case, the water flows naturally intoFU 4. However, with a minor intervention, its flow could occasion-ally be diverted towards FUs 1–2–3. This intervention would bereversible and it is planned to go into effect only in cases of emer-gency inflows and not on a continuous basis. It is not our intentionto distort the functioning of the Park. Fig. 10a shows what wouldhappen if, in addition to the net effluent inflow from the Azuer line,this water surplus were applied in a ‘‘step-by-step application’’ toFUs 1–2–3. In the model, when FU 5 reaches the full inundationcondition, QO of FU 5 becomes non-null. Its value is assumed tobe equal to the surplus, and it is added to TSE inflow of the Azuerline to obtain the value of QI to be considered in the simulation ofFUs 1–2–3. In this simulation, values of KM1–123 and KM2–123 fromTable 3 were used. Full inundation of FUs 1–2–3 (NIA of 96 ha,and EIA of about 138 ha) is achieved in approximately half of theyears of simulation. The net inundated area ranges from 30 to96 ha. This ensures the full inundation of FU 2, the Guadiana river-bed where the peat bogs are mainly located.

To complete this simulation exercise, calculations were made tofind out what would happen if the net effluent from Fuente el Fres-no along with the small surplus discharges from FUs 1–2–3 (‘‘step-by-step application’’) were applied to FU 4. The values of KM1–4 andKM2–4 identified in Table 3 were used. The results are given in Fig.10b. Full inundation (NIA of 26 ha, EIA of 45 ha) is only achieved in

Fig. 10a. Evolution of the inundated area in FUs 1-2-3 after applying the surplusTSE resulting from the inundation of FU 5 in addition to the TSE from the Azuer line.

Fig. 10b. Evolution of the inundated area in FU 4 after applying the surplus TSEresulting from the inundation of FUs 1–2–3 in addition to the TSE from Fuente elFresno.

Fig. 11. Estimation of the evolution of the inundated area in FU 5 assuming that theinundated area is zero at that start of each hydrologic year.

V. Navarro et al. / Journal of Hydrology 401 (2011) 53–64 63

extraordinarily heavy rainfall events. However, the inundation of aminimum area, associated with the surface depressions of theGigüela riverbed, is guaranteed.

As discussed in the previous section, although these simulationsmust be interpreted with caution, they do, however, illustrate thatthe application of TSE is sufficient to substantially improve thestate of TDNP.

This fact was also highlighted by simulating the response thatFU 5 would have, year by year, if, in addition to maintaining theTSE distribution defined above, the inundated area was assumedto be zero at the start of each hydrologic year. As indicated inFig. 11, with the contributions from only one year, it is possibleto ensure that in the worst year (hydrologic year 2019–2020, pre-cipitation 248.2 mm, 9.7th percentile with respect to data from1959) the mean inundation of FU 5 will be 62.5% (62.3 ha), whereasthe inundation of FUs 1–2–3 will be 79.3% (73.6 ha), and in FU 4 itwill be 18% (4.6 ha). This simulation is especially interesting, sinceit is not a sensitivity analysis, but rather an estimation of the actualbehaviour. Despite all the limitations discussed earlier, it allows forthe verification of the rapid efficiency of TSE application. This quickresponse would be slowed down if the initial dry condition wereassociated with a drought that had caused a great reduction in soil

moisture. Under these conditions, both soil suction and the pres-ence of cracks would play an important role in infiltration, an effectthat has not been considered here, and the speed of the inundationresponse would be lower that expected. The application of TSEwould help prevent the occurrence of situations of this nature,which are highly unusual in the hydroperiod typical of TDNP priorto the intensive water abstraction that has been carried out in theWest Mancha aquifer since the late 1970s (Álvarez-Cobelas et al.,2001).

6. Conclusions

An analysis of the inundation data and the digital elevationmodel provided by the TDNP-TS enabled us to develop a simplifiedconceptual model of the hydrologic behaviour of Las Tablas. Thismodel defined six functional units represented in Fig. 3. An analy-sis of the inundation of the first 5 was considered to be of mostinterest. A linear decrease of the mean effective hydraulic conduc-tivity with the elevation was assumed to perform the analysis bymeans of a dynamic water budget. Twelve drying processes wereused to characterise the parameters of this law. Inundation datagathered by the TDNP-TS was used. The quality of the identifica-tion processes (Fig. 7), as well as the adjustments made to the cal-ibration simulations (Fig. 8), conferred a certain degree ofconfidence on both the parameters identified (Table 3) and onthe hydrologic model put forth. For this reason, although, as com-monly occurs in ecological engineering, the variability of the sys-tem advises caution in interpreting the results from thesimulations, it has been decided to use this model to evaluatethe long-term response of the system to TSE application. Even ifa dry climate is assumed to exist, Figs. 9–11 were obtained, whichindicates that the application of TSE will produce a significant in-crease in the inundation of FUs 1–2–3, 4 and 5. Therefore, elementsof judgement were introduced that show the advisability, from ahydrologic point of view, of applying TSE to TDNP.

Acknowledgements

The authors would like to thank the Confederación Hidrográficadel Guadiana for providing the means and the financial support tocarry out this study. We are especially grateful for the support pro-vided by Mr. Samuel Moraleda. This research was also financed inpart by a Research Grant awarded to Ms. Garcia by the SpanishMinistry of Science and Education research grant BES-2006-

64 V. Navarro et al. / Journal of Hydrology 401 (2011) 53–64

12639. Also gratefully acknowledged is the financial supportprovided by the Education and Research Department of theCastilla-La Mancha Regional Government and the EuropeanSocial Fund within the framework of the Integrated OperativeProgramme for Castilla-La Mancha 2000–2006 (approved byCommission Decision C(2001) 525/1) to Mr. Sánchez. The financialsupport provided by the Spanish Ministry of Education through theFPU Program PhD Grant AP2009-2134 awarded to Ms. Asensio isgratefully acknowledged as well. The support provided by the staffof Las Tablas de Daimiel National Park, especially by Mr. CarlosRuiz, is also greatly appreciated. Lastly, we thank Dr. Florín,Dr. Cirujano and Dr. Álvarez-Cobelas for their valuable suggestions.

References

Allen, R.G., Pereira, L.S., Raes, D., Smith, M., 1998. Crop evapotranspiration.Guidelines for computing crop water requirements. FAO irrigation anddrainage paper 56. Food and Agriculture Organization of the United Nations,Rome.

Allen, T.F.H., Giampietro, M., Little, A.M., 2003. Distinguishing ecologicalengineering from environmental engineering. Ecological Engineering 20 (5),389–407.

Álvarez-Cobelas, M., Cirujano, S., 2007. Multilevel responses of emergent vegetationto environmental factors in a semiarid floodplain. Aquatic Botany 87 (1), 49–60.

Álvarez-Cobelas, M., Cirujano, S., Sánchez-Carrillo, S., 2001. Hydrological andbotanical man-made changes in the Spanish wetland of Las Tablas deDaimiel. Biological Conservation 97 (1), 89–98.

Álvarez-Cobelas, M., Sánchez-Carrillo, S., Cirujano, S., Angeler, D.G., 2008. Long-termchanges in spatial patterns of emergent vegetation in a Mediterraneanfloodplain, Natural versus anthropogenic constraints. Plant Ecology 194 (2),257–271.

Bouwer, H., 1986. Intake rate: cylinder infiltrometer. In: Klute, A. (Ed.), Methods ofSoil Analysis: Part I, Physical and Mineralogical Methods. AgronomyMonograph No. 9. American Society of Agronomy, Soil Science Society ofAmerica, Madison, Wisconsin, USA, pp. 825–844.

Bradley, C., 2002. Simulation of the annual water table dynamics of a floodplainwetland, Narborough Bog, UK. Journal of Hydrology 261 (1–4), 150–172.

Bromley, J., Cruces, J., Acreman, M., Martínez, L., Llamas, M.R., 2001. Problems ofsustainable groundwater management in an area of over-exploitation: theUpper Guadiana Catchment, Central Spain. International Journal of WaterResources Development 17 (3), 379–396.

Brooks, R.T., 2005. A review of basin morphology and pool hydrology of isolatedponded wetlands: implications for seasonal forest pools of the northeasternUnited States. Wetlands Ecology and Management 13 (3), 335–348.

Brush, C.F., Belitz, Kenneth, Phillips, S.P., 2004. Estimation of a water budget for1972–2000 for the Grasslands area, central part of the western San JoaquinValley, California. US Geological Survey Scientific Investigations Report2004–5180.

Candela, L., von Igel, W., Elorza, F.J., Aronica, G., 2009. Impact assessment ofcombined climate and management scenarios on groundwater resources andassociated wetland (Majorca, Spain). Journal of Hydrology 376 (3–4), 510–527.

Castaño, S., 2003. Estudio metodológico para el cálculo de la infiltración en el vasode Las Tablas de Daimiel. Validación de resultados. Ph.D. Thesis, UniversidadComplutense de Madrid.

Castaño-Castaño, S., Martínez-Santos, P., Martínez-Alfaro, P.E., 2008. Evaluatinginfiltration losses in a Mediterranean wetland: Las Tablas de Daimiel NationalPark, Spain. Hydrological Processes 22 (26), 5048–5053.

Cesanelli, A., Guarracino, L., 2009. Estimation of actual evapotranspiration bynumerical modeling of water flow in the unsaturated zone: a case study inBuenos Aires, Argentina. Hydrogeology Journal 17 (2), 299–306.

Cirujano, S., Casado, C., Bernués, M., Camargo, J.A., 1996. Ecological study of LasTablas de Daimiel National Park (Ciudad Real, Central Spain): Differences inwater physico-chemistry and vegetation between 1974 and 1989. BiologicalConservation 75 (3), 211–215.

Conan, C., de Marsily, G., Bouraoui, F., Bidoglio, G., 2003. A long-term hydrologicalmodelling of the Upper Guadiana river basin (Spain). Physics and Chemistry ofthe Earth, Parts A/B/C 28 (4-5), 193–200.

Custodio, E., 2002. Aquifer overexploitation: what does it mean? HydrogeologyJournal 10 (2), 254–277.

Dalton, M.S., Aulenbach, B.T., Torak, L.J., 2004. Ground-water and surface-water flowand estimated water budget of Lake Seminole, southwestern Georgia, and

northwestern Florida. US Geological Survey, Scientific Investigations Report2004-5073.

Florín, M., Montes, C., Rueda, F., 1993. Origin, hydrologic functioning, andmorphometric characteristics of small, shallow, semiarid lakes (Lagunas) in LaMancha, central Spain. Wetlands 13 (4), 247–259.

Fornes, J., Rodriguez, J.A., Hernandez, N., Llamas, M.R., 2000. Possible solutions toavoid conflicts between water resources development and wetlandconservation in the ’’La Mancha Humeda’’ Biosphere Reserve (Spain). Physicsand Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere 25,623–627.

Gasca, D., Ross, D., 2009. The use of wetland water balances to link hydrogeologicalprocesses to ecological effects. Hydrogeology Journal 17 (1), 115–133.

Healy, R.W., Winter, T.C., LaBaugh, J.W., and Franke, O.L., 2007, Water budgets:Foundations for effective water-resources and environmental management: USGeological Survey Circular 1308.

Lindley, M.R., Barfield, B.J., Wilson, B.N., 1995. Surface impoundment element modeldescription. NSERL Report 11. In: Flanagan, D.C., Nearing, M.A. (Eds.), USDA–Water Erosion Prediction Project (WEPP). USDA–ARS National Soil ErosionResearch Laboratory, West-Lafayette, Indiana, USA.

Llamas, M., 1988. Conflicts between wetland conservation and groundwaterexploitation: Two case histories in Spain. Environmental Geology 11 (3),241–251.

Lott, R.B., Hunt, R.J., 2001. Estimating evapotranspiration in natural and constructedwetlands. Wetlands 21 (4), 614–628.

Merritt, M.L., Konikow, L.F., 2000. Documentation of a computer program tosimulate lake-aquifer interaction using the Modflow ground-water flow modeland the Moc3D solute-transport model, US Geological Survey, Water-ResourcesInvestigations Report 00-4167.

Mitchell, J.K., Engel, B.A., Srinivasan, R., Wang, S.S.Y., 1993. Validation of AGNPS forsmall watershed using an integrated AGNPS/GIS system. Journal of theAmerican Water Resources Association 29 (5), 833–842.

Moreno, J.M., (Ed.), 2005. Evaluación preliminar de los impactos en España porefecto del cambio climático. Ministerio de Medio Ambiente. Madrid.

Neumaier, A., 2004. Complete search in continuous global optimization andconstraint satisfaction. Acta Numerica 13 (1), 271–369.

NRCS, 2003. National Engineering Handbook. Section 4: Hydrology. National SoilConservation Service, United States Department of Agriculture, Washington,DC, USA.

Pachepsky, Y.A., Guber, A.K., Van Genuchten, M.T., Nicholson, T.J., Cady, R.E.,Simunek, J., Schaap, M.G., 2006. Model Abstraction Techniques for Soil-WaterFlow and Transport. NUREG/CR-6884, US Nuclear Regulatory Comission,Washington, DC, USA.

Press, W.H., Teulowsky, S.A., Vetterling, W.T., Flannery, B.P., 2002. The Grid:Numerical Recipes in C++: The Art of Scientific Computing. CambridgeUniversity Press, Cambridge.

Ruano, P., 1996. Proyecto de captación y aplicación de aguas subterráneas parasituaciones de emergencia en el Parque Nacional de Las Tablas de daimiel.Memoria del estudio hidrológico, TRAGSATEC, Madrid.

Sánchez-Carrillo, S., Angeler, D.G., Sánchez-Andrés, R., Alvarez-Cobelas, M.,Garatuza-Payán, J., 2004. Evapotranspiration in semi-arid wetlands:Relationships between inundation and the macrophyte-cover:open-waterratio. Advances in Water Resources 27 (6), 643–655.

Sánchez-Carrillo, S., Álvarez-Cobelas, M., Angeler, D.G., 2001a. Sedimentation in thesemi-arid freshwater wetland Las Tablas de Daimiel (Spain). Wetlands 21 (1),112–124.

Sánchez-Carrillo, S., Álvarez-Cobelas, M.A., Angeler, D.G., Vizcayno-Muñoz, C.,2001b. Tasas de acreción y características de los sedimentos actuales en elParque Nacional de Las Tablas de Daimiel (Ciudad Real). Estudios Geológicos 56,239–250.

Saxton, K.E., Willey, P.H., 2006. The SPAW model for agricultural field and pondhydrologic simulation. In: Singh, V.P., Frevert, D. (Eds.), Mathematical Modelingof Watershed in Hydrology. CRC Press, pp. 401–435.

Scanlon, B.R., Christman, M., Reedy, R.R., Porro, I., Simunek, J., Flerchinger, G.N.,2002. Intercode comparisons for simulating water balance of surficialsediments in semiarid regions. Water Resources Research 38 (12), 1323.doi:10.1029/2001WR001233.

Vigiak, O., van Dijck, S.J.E., van Loon, E.E., Stroosnijder, L., 2006. Matching hydrologicresponse to measured effective hydraulic conductivity. Hydrological Processes20 (3), 487–504.

Walton, R., Chapman, R.S., Davis, J.E., 1996. Development and application of thewetlands dynamic water budget model. Wetlands 16 (3), 347–357.

Young, D.F., Carleton, J.N., 2006. Implementation of a probabilistic curve numbermethod in the PRZM runoff model. Environmental Modelling and Software 21(8), 1172–1179.