Invest Model-Based Spatiotemporal Analysis of Water Supply Services in the Zhangcheng District

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Article InVEST Model-Based Spatiotemporal Analysis of Water Supply Services in the Zhangcheng District

Run Liu 1,2,3, Xiang Niu 1,2,3,*, Bing Wang 1,2,3 and Qingfeng Song 1,2,3

1 Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China; [email protected] (R.L.); [email protected] (B.W.); [email protected] (Q.S.) 2 Key Laboratory of Forest Ecology and Environment, State Forestry and Grassland Administration, Beijing 100091, China 3 Dagangshan National Key Field Observation and Research Station for Forest Ecosystem, Xinyu 338033, China * Correspondence: [email protected]; Tel.: +86-10-6288-9334

Abstract: The Zhangcheng District is critically responsible for protecting water resources, preserving sand sources, and improving the ecological environment in Beijing. Quantitative evaluation and research on the ecosystem water supply services in this area are beneficial for developing conservation planning and establishing ecological compensation mechanisms in water conservation areas. In this paper, based on the land use, meteorological, soil, and field observation data of the research area, the InVEST water yield model is used to estimate the water supply of the ecosystem in the Zhangcheng District. The model quantitatively analyzes the spatiotemporal distribution characteristics of water supply services in the basin and the influence of different topographic factors. The results show that the average supply of ecosystem water in the Zhangcheng District is approximately 45 mm, and there

is a degree of spatial heterogeneity. The total water supply in the Zhangcheng District is relatively small. The water resource supply in the southwest is relatively small, the rainfall in mountainous

Citation: Liu, R.; Niu, X.; Wang, B.; forest areas in the southeast is high, its water supply is higher, and the supply of forest land water is ◦ ◦ Song, Q. InVEST Model-Based relatively high. The high-value areas are mainly distributed at 1500 to 3500 m and 15 ~40 ; the water Spatiotemporal Analysis of Water supply on the sunny slope is greater than that on the shady slope. With the increase in altitude and Supply Services in the Zhangcheng slope, the water supply in the basin tends to increase ﬁrst and then decrease. District. Forests 2021, 12, 1082. https://doi.org/10.3390/f12081082 Keywords: InVEST model; water supply function; ecosystem services; Zhangcheng District

Academic Editor: Manuel Esteban Lucas-Borja 1. Introduction Received: 30 May 2021 Forest water conservation has become one of the most crucial issues in forest ecosys- Accepted: 19 July 2021 Published: 13 August 2021 tems [1]. Moreover, the forest canopy, detritus layer, and soil layer are regularly recognized as the main redistribution areas [2,3] that effectively conserve soil moisture and regulate

Publisher’s Note: MDPI stays neutral river ﬂow [4,5]. Water resource supply is important in maintaining regional biodiversity with regard to jurisdictional claims in and other key ecosystem functions [6,7], affecting the region’s population, socio-economic published maps and institutional afﬁl- development, and layout [8]. With global climate change, surface water shortages, and the iations. rapid deterioration of the water environment [9,10], quantitative spatial and visual assessment of the water supply capability of regional ecosystems is one of the most important research topics in hydrology and ecology [11–13]. With the development of remote sensing GIS technology and hydrological models [14], more scholars have tried to quantitatively visualize, accurately analyze, and evaluate the Copyright: © 2021 by the authors. function of regional ecosystems through model simulation methods. Simulation methods Licensee MDPI, Basel, Switzerland. This article is an open access article include the MIKE System Hydrological European (MIKE SHE) model [15], Temperature distributed under the terms and Vegetation Dryness Index model (TVDI) [16], Soil and Water Assessment Tool (SWAT) conditions of the Creative Commons model [17], Soil Conservation Service Curve Number method (SCS-CN) model [18], and Attribution (CC BY) license (https:// Integrate Valuation of Ecosystem Services and Tradeoffs (InVEST) model [19]. The InVEST creativecommons.org/licenses/by/ model quantitatively estimates the water supply of different landscapes based on the water 4.0/). balance principle, considering the spatial differences in soil permeability and topography

Forests 2021, 12, 1082. https://doi.org/10.3390/f12081082 https://www.mdpi.com/journal/forests Forests 2021, 12, 1082 2 of 15

under different land uses [13,20–22]. The parameters and characteristic data requirements of the model are low [23], and it can use empirical parameters and quantify ecosystem service functions in the form of thematic maps [24]. Thus far, the InVEST model has been successfully applied by scholars in the assessment of regional ecosystem services on the north coast of O’ahu Island, Hawaii [25], the San Pedro River basin in Arizona [26], the Beijing mountains [4], the upper reaches of the Han River [27], Sanjiangyuan [28], and other regional ecosystem services. However, due to the large geographical and environmental differences between regions, it is crucial to adjust the model parameters according to each research area’s characteristics, especially in large- and medium-scale areas where comprehensive field monitoring data are lacking [29]. Simultaneously, significant spatial and temporal differences in the water supply capacity of different ecosystems are closely related to factors such as precipitation, evaporation, land use/overlay changes, topography, soil permeability, and vegetation transpiration [22]. For example, different vegetation types (or ecosystems) have different effects on hydrological factors [30], such as rainfall interception, seepage, evaporation, the distribution and growth status of vegetation, and topographic factors (such as slope direction and altitude), which indirectly or directly affect the spatial pattern of the water supply [31]. Therefore, this paper analyzes the spatial and temporal differentiation characteristics in different ecosystems and clarifies the relationship between water supply and meteorological factors, topographic factors, and land use. Moreover, to provide an important reference for ecological environment construction and protection in the Zhangcheng District, the key driving factors affecting changes in the water supply are examined. The cities of Zhangjiakou and Chengde (referred to as the Zhangcheng District) are located in the northern part of Beijing and are key in protecting Beijing’s water sources, preserving sand sources, and improving the ecological environment. However, due to special location characteristics and historical reasons, the economic development of the Zhangcheng District is relatively slow, regional ecological poverty is prominent, and ecosystem services such as water supply function in river basins are changing, triggering new ecological and environmental problems. Therefore, it is crucial to quantify the water supply service function and the spatial and temporal distribution characteristics of watershed water supply services in the Zhangcheng District. This will clarify the different characteristics of water supply services in different ecosystems and different topographies to provide quantitative visual evaluation results and a scientific basis for key functional zoning, ecological restoration, and ecological compensation of water supply in river basins.

2. Research Method and Data Processing 2.1. Research Site The Zhangcheng District is located in northern Hebei Province (113◦500~119◦150 E, 39◦300~42◦400 N). The topography of this area mainly consists of the dam plateau area, the northern Hebei mountain area, and the low hills in northwest Hebei, with the overall terrain gradually decreasing from northwest to southeast (Figure1a). It belongs to the temperate continental monsoon climate and is characterized by four distinct seasons. The average temperature, precipitation, and potential evaporation in the upper plateau area of the dam are −1~2 ◦C, 300~400 mm, and 1400 mm, respectively. Due to the inﬂuence of topography and latitude, the temperature in the mountains near the dam gradually increases from north to south, and the average temperature and precipitation are 5~9 ◦C and 400~600 mm, respectively. Zhangjiakou City contains ﬁve major water systems: the Yongding River, Chaobai River, Daqing River, Taiqing River, and Inland River. Chengde City employs the province’s three northern rivers (tidal white river, white river, thistle canal), Liaohe, and Daling River as water systems. The total water resources in the Zhangcheng District amount to 5.497 × 108 m3, of which 4.792 × 108 m3 are surface water resources, 2.873 × 108 m3 are groundwater resources, and the double-calculated water volume is 2.169 × 108 m3. In 2015, the forest area in the Zhangcheng District was 4.6607 × 106 hm2. Forest resources are rich and diverse and have evident horizontal and vertical distribution rules. There Forests 2021, 12, x FOR PEER REVIEW 3 of 15

400~600 mm, respectively. Zhangjiakou City contains five major water systems: the Yong- ding River, Chaobai River, Daqing River, Taiqing River, and Inland River. Chengde City employs the province’s three northern rivers (tidal white river, white river, thistle canal), Liaohe, and Daling River as water systems. The total water resources in the Zhangcheng District amount to 5.497 10 m, of which 4.792 10 m are surface water resources, 2.873 10 m are groundwater resources, and the double-calculated water volume is Forests 2021, 12, 1082 3 of 15 2.169 10 m. In 2015, the forest area in the Zhangcheng District was 4.6607 10 hm. Forest resources are rich and diverse and have evident horizontal and vertical distribution rules. There are forests, grasslands, farmland, water, and other ecosystems in the area. Forestare forests,and grassland grasslands, ecosystems farmland, mainly water, include and other Picea ecosystems asperata Mast, in the Quercus, area. Forest Betula, and Larix grassland ecosystems mainly include Picea asperata Mast, Quercus, Betula, Larix principis- principis-rupprechtii Mayr, Pinus sylvestris, and Pinus tabulaeformis Carr, which play a cru- rupprechtii Mayr, Pinus sylvestris, and Pinus tabulaeformis Carr, which play a crucial role in cialwater role conservation.in water conservation.

a b

FigureFigure 1. 1.TheThe location location (a (a)) and and land useuse type type (b ()b of) of the the study study area. area. 2.2. InVEST Water Supply Service Model Method 2.2. InVEST Water Supply Service Model Method The InVEST model of water supply service (also known as a water production module)The is aInVEST raster-based model water of water balance supply estimation service module (also [ 32known,33]. Moreover, as a water the production relationship module)between is a raster-based climate, terrain water factors, balance and estimation water circulation module simplifies [32,33]. theMoreover, converging theprocess. relationship betweenAssuming climate, that theterrain grid factors, water service and water reaches circulation the outlet simplifies in any of thethe aboveconverging ways, theprocess. Assumingamount ofthat water the supplied grid water to each service grid cell reache (includings the outlet surface in production any of the flow, above soil waterways, the amountcontent, of drywater matter supplied holding to capacity,each grid and cell cover (including flow) equals surface the production sedimentation. flow, By soil sub- water tracting the actual evaporation and simulating the spatial distribution of the regional water content, dry matter holding capacity, and cover flow) equals the sedimentation. By sub- supply [13,34–36], the specific calculation formula is as follows: tracting the actual evaporation and simulating the spatial distribution of the regional water supply [13,34–36], the specific calculationAET formulaxj is as follows: Y = 1 − × P (1) jx P x x 1 (1) AETxj 1 + w R = x x (2) 1 1 Px 1 + wx Rx + Rxj 1 (2) 1 Z·AWCx wx = (3) Px ∙ (3) Kxj·ET0 Rx = (4) Px ∙ (4) AWCx = min(MSDx, RDx) × PAWCx (5)

Type Yjx is a landscape typej min (with upper grid, unit)x annual water supply service (5) (m3); AET is the type j upper grid unit x annual average evaporation emission; P is the Type xj is a landscape type j with upper grid unit x annual water supplyx service average annual rainfall of the grid unit x; Z is the Zhang coefﬁcient, also known as the 3 (mseasonal); factor, is the which type isj upper a constant grid ranging unit x fromannual 1 to average 10 that characterizesevaporation the emission; average is theprecipitation average annual characteristics rainfall of of the multiple grid yearsunit x determined; Z is the Zhang by the coefficient, seasonal time also distribution known as the and rainfall. For areas where rainfall is concentrated during winter, the Z-value tends towards 10, and for areas where rainfall is distributed throughout the year or in summer, the Z-value tends towards 1; wx is a non-physical parameter that characterizes the natural climate–soil properties and is dimensionless; Rxj is the drying index of the grid element Forests 2021, 12, x FOR PEER REVIEW 4 of 15

seasonal factor, which is a constant ranging from 1 to 10 that characterizes the average precipitation characteristics of multiple years determined by the seasonal time distribution and rainfall. For areas where rainfall is concentrated during winter, the Z-value tends towards 10, and for areas where rainfall is distributed throughout the year or in summer, the Z-value tends towards 1; is a non-physical parameter that characterizes the natural climate–soil properties and is dimensionless; Rxj is the drying index of the grid element

Forests 2021, 12, 1082 x on landscape type j and is dimensionless [37]; is the water content available4 of 15 to plants; is the potential dispersion (mm); is the crop coefficient, which is the ratio of the ET of landscape type j on the grid element x to potential dispersion , which is

alsox oncalled landscape the vegetation type j and disper is dimensionlesssion coefficient [37]; AWCin thex ismodel; the water content is the available maximum to soil depth;plants; ET 0 isis the the root potential depth; dispersion (mm); is theK availablexj is the crop water coefﬁcient, available which through is the ratioindirect of cal- culationthe ET of of soil landscape texture type [38]j on. the grid element x to potential dispersion ET0, which is also called the vegetation dispersion coefﬁcient in the model; MSDx is the maximum soil depth; 2.3.RD Datax is Processing the root depth; PAWCx is the available water available through indirect calculation of soil texture [38]. InVEST water supply service model input parameters include rainfall, potential evaporation,2.3. Data Processing land use/overburden type, soil thickness, effective soil moisture content, and a biophysicalInVEST parameter water supply table. service model input parameters include rainfall, potential 1. evaporation,Annual rainfall land use/overburden (P) was calculated type, soil based thickness, on the effective rainfall soil data moisture of meteorological content, and sta- a biophysicaltions in and parameter around table.the Zhangcheng District (18 stations) from 1990 to 2020, and the 1. dataAnnual from rainfall the National (P) was calculatedMeteorological based on Sc theience rainfall Data data Center of meteorological (http://data.cma.cn/ac- stations cessedin and on around 12 August the Zhangcheng 2021). Using District the Krigin (18 stations)g method from to 1990 interpolate to 2020, andrainfall the data data, the spatialfrom distribution the National Meteorologicalraster data of Sciencethe average Data Centerrainfall (http://data.cma.cn/ in the research area accessed for multiple on 12 August 2021). Using the Kriging method to interpolate rainfall data, the spatial years were obtained (Figure 2a). distribution raster data of the average rainfall in the research area for multiple years 2. Potentialwere obtained evaporation (Figure (2a).). The improved Hargreaves formula, one of the simplest 2. empiricalPotential formulas evaporation for (ETcalculating0). The improved potential Hargreaves steam emission formula, E, one was of the adopted. simplest Using thisempirical formula formulas is morefor reliable calculating when potential there are steam more emission uncertainties E, was adopted. than the Using Penman– Monteiththis formula formula is more [39–43]. reliable when there are more uncertainties than the Penman– Monteith formula [39–43]. . 0.003 0.408 ( 17) ( 0.0123) 0.76 ET0 = 0.003 × 0.408 × RA × (Tav + 17) × (TD − 0.0123P) In the improved Hargreaves formula, (in °C) is the average maximum and lowest ◦ temperatureIn the improvedper day, TD Hargreaves is the difference formula, T betweenav (in C) the is the two average temperatures, maximum RA and is lowest the astro- nomicaltemperature radiation per ( day,unit: TD MJm is thed difference), P represents between theprecipitation two temperatures, (unit: mm/month). RA is the as- Tem- −2 −2−1 peraturetronomical and radiationprecipitation (unit :dataMJm wered obtained), P represents from the precipitation National (Meteorologicalunit : mm/month). Science DataTemperature Center (http://data.cma.cn/accessed and precipitation data were obtainedon 12 August from the 2021); National RA numbers Meteorological were obtained Sci- by encethe regression Data Center line (http://data.cma.cn/ method of correction accessed (Figure on 122b). August 2021); RA numbers were obtained by the regression line method of correction (Figure2b). a b

ET FigureFigure 2. Precipitation 2. Precipitation (a ()a and) and 0((bb)) spatial spatial distributionsdistributions in in the the Zhangcheng Zhangcheng District. District. 3. Land use type (LUCC) was obtained through the Geographic Data Sharing Infras- tructure of the Resource and Environment Science and Data Center (http://www. resdc.cn/, accessed on 12 August 2021). It mainly uses Land-sat remote sensing image data as the primary information source and the land use/land cover remote sensing monitoring database (CNLUCC) established through visual interpretation, Forests 2021, 12, x FOR PEER REVIEW 5 of 15

3. Land use type (LUCC) was obtained through the Geographic Data Sharing Infra- structure of the Resource and Environment Science and Data Center (http://www.resdc.cn/, accessed on 12 August 2021). It mainly uses Land-sat remote sensing image data as the primary information source and the land use/land cover remote sensing monitoring database (CNLUCC) established through visual interpretation, combined with the actual landscape types of the research area. Here, the land Forests 2021, 12, 1082 use type was divided into 12 subcategories in six categories, namely5 cultivated of 15 land, forest land (forest land, shrubland, sparse forest land, other woodlands), grassland (high-covered grassland, medium-cover grassland, low-cover grassland), water combined(river, lake, with and the reservoir), actual landscape construction types of theland, research and unused area. Here, land the (sandland, land use bare land, type was divided into 12 subcategories in six categories, namely cultivated land, and high Mountain snow-naked rock) (Figure 1b). forest land (forest land, shrubland, sparse forest land, other woodlands), grassland 4. (high-coveredWater content grassland, available medium-cover to plants (%). grassland, The available low-cover grassland),water content water of (river, plants was cal- lake,culated and using reservoir), the constructionmethod proposed land, and by unused Gupta land [38]. (sandland, The calculation bare land, formula and is as fol- highlows: Mountain snow-naked rock) (Figure1b). 4. Water content available to plants (%). The available water content of plants was calculated usingPAWC the method 54.509 proposed 0.132 by Gupta [0.00338]. The calculation 0.055 formula 0.006 is as follows: PAWC = 54.509 − 0.132sand 0.738− 0.003sand 2 0.007− 0.055silt −0.006 2.688silt2 0.501 −0.738clay + 0.007clay2 − 2.688OM + 0.501OM2 IIn the formula, sand, silt, and clay represent the content of sand, powder, and clay in theIn thesoil formula, (%), and sand, OM silt, is the and organic clay represent matter the of content the soil of (%). sand, Soil powder, data and(HWSD clay V1.2) only in the soil (%), and OM is the organic matter of the soil (%). Soil data (HWSD V1.2) only provideprovide soil soil organic organic carbon carbon content. content. Therefore, Therefore, to obtain to soil obtain organic soil matter organic content, matter the content, the biommelembiommelem coefﬁcient coefficient was was used used to convert to convert soil organic soil organic carbon content carbon to content soil organic to soil organic mattermatter content. content. The The above above method method was used was toused obtain to theobtain water the available water toavailable plants in to the plants in the ZhangchengZhangcheng District District (Figure (Figure3). 3).

FigureFigure 3. 3.Plant Plant available available water water content content in the in Zhangcheng the Zhangcheng District. District. 5. Biophysical parameters table. The biophysical parameters table reflects the proper- 5. tiesBiophysical of land use parameters and land cover table. types The in biophysi the studycal area, parameters including landtable use reflects coding, the proper- maximumties of land root use depth and ofland vegetation, cover types and evaporationin the study coefficient. area, including The maximum land use coding, rootmaximum depth of root vegetation depth of data vegetation, and the dispersion and evaporation coefficient coefficient. were obtained The from maximum root previousdepth of research vegetation results data [41 and]. Food the anddispersi Agricultureon coefficient Organization were ofobtained the United from previ- Nations (FAO) reference values for evapotranspiration coefficients (crop coefficients) (oushttp://www.FAO.org/docrep/x0490E/x0490e00.htm/ research results [41]. Food and Agriculture, Organiza accessed ontion 12 Augustof the United 2021) Nations and(FAO) InVEST reference model values database for data evapotranspiration were generated from coefficients dbf data by (crop land coefficients) use type (landscape(http://www.FAO.org/docrep/x0490E/x0490e0 type). 0.htm/, accessed on 12 August 2021) 3. Resultsand InVEST model database data were generated from dbf data by land use type 3.1. Model(landscape Parameter type). Calibration It is difficult to accurately verify the prediction results of the model water supply module of InVEST. To verify the accuracy of the simulation results, this study uses Hebei Water Statistics Bulletin data from 1995 to 2015 to determine and validate the relevant parameters of the model; it was used for model parameter calibration in 1995, 2005, and Forests 2021, 12, 1082 6 of 15

2015, and for model validation in 2010 and 2015. The Zhang coefﬁcient is based on the precipitation–runoff relationship to obtain the average natural runoff. It is estimated according to the principle that numerically connects the natural runoff. When the Zhang coefﬁcient is 6.8, the model simulation depth is the closest to the actual water production depth, and the relative error remains within 20%, indicating that the model parameter calibration is preferable.

3.2. Model Verification This study used the meteorological and land use data of five periods between 1995 and 2015 as input for simulation calculation and compared them with the obtained actual data to verify that the expected model performance was less than 20% (Table1). The comprehensive verification results show that in 20 years, the total simulated water production volume and the actual water production in Zhangjiakou City and Chengde City in 2015 are 7.73% and 4.83%, respectively, with an error of 3.73% for Chengde City and 0% in Zhangjiakou City. Thus, the InVEST model has good simulation accuracy, the parameter effect is more robust, and it can estimate the water production volume in the Zhangcheng District.

Table 1. Annual water yield model result veriﬁcation of the InVEST model.

Model Simulated Actual Water Relative Accuracy Year City Water Depth Depth (mm) Error (%) Veriﬁcation (mm) Zhangjiakou 42.63 36.76 15.97 1995 Chengde 42.96 42.29 12.20 Corrected Zhangjiakou 44.14 37.32 18.27 2000 parameter Chengde 46.04 44.69 13.18 Zhangjiakou 43.57 37.88 15.01 2005 Chengde 44.76 40.64 10.14 Zhangjiakou 43.10 46.00 6.30 2010 Veriﬁed Chengde 45.48 47.20 3.64 result Zhangjiakou 42.20 42.20 0.00 2015 Chengde 44.80 38.90 3.73

3.3. Characteristics of Spatial–Temporal Distribution of Water Supply Services in Zhangcheng District Figure4 shows that the spatial distribution pattern of water supply services in the Zhangcheng District has minor changes and generally shows regularity. The high-value water supply service zones are concentrated in Huai’an County, Guyuan County, Zhangjiakou City, Xinglong County, and Pingquan County, southern Chengde City. The average water supply service is between 60 and 85 mm; on both sides of the Yanshan-Tahang Mountains, the average water supply service is between 31 and 59 mm. Located in Yanshan-Taihang Mountains, Weichang County, Longhua County, and Zhuolu County, the average water supply service is relatively small, with 20~30 mm. This distribution pattern is related directly to the average annual precipitation and vegetation distribution in the Zhangcheng District. In other words, the regions with high annual precipitation and low vegetation evaporation have a strong water supply capacity. In terms of time, the average water production during the study tended to increase and then decrease; the total water production in Zhangjiakou and Chengde cities increased from 15.60 × 108 m3 and 16.84 × 108 m3 in 1995a to 15.94 × 108 m3 and 17.55 × 108 m3 in 2005, and then decreased to 15.45 × 108 m3 and 17.60 × 108 m3 in 2015. Forests 2021, 12, x FOR PEER REVIEW 7 of 15 Forests 2021, 12, x FOR PEER REVIEW 7 of 15

water supply service zones are concentrated in Huai’an County, Guyuan County, Zhang- water supply service zones are concentrated in Huai’an County, Guyuan County, Zhang- jiakou City, Xinglong County, and Pingquan County, southern Chengde City. The aver- jiakou City, Xinglong County, and Pingquan County, southern Chengde City. The average water supply service is between 60 and 85 mm; on both sides of the Yanshan-Tahang age water supply service is between 60 and 85 mm; on both sides of the Yanshan-Tahang Mountains,Mountains, thethe averageaverage waterwater supply servicservicee isis betweenbetween 31 31 and and 59 59 mm. mm. Located Located in in Yanshan-TaihangYanshan-Taihang Mountains, Mountains, Weichang CounCounty,ty, Longhua Longhua County, County, and and Zhuolu Zhuolu County, County, thethe average average water water supplysupply serviceservice isis relativelyrelatively small,small, with with 20~30 20~30 mm mm . This. This distribution distribution patternpattern is is related related directly directly toto the average annuannualal precipitation precipitation and and vegetation vegetation distribution distribution inin the the Zhangcheng Zhangcheng District.District. In other words,words, thethe regions regions with with high high annual annual precipitation precipitation andand low low vegetation vegetation evaporation evaporation have aa strongstrong water water supply supply capacity. capacity. In In terms terms of oftime, time, the the averageaverage water water production production duringduring the studystudy tended tended to to increase increase and and then then decrease; decrease; the the total total 10 10 m m Forests 2021, 12, 1082 waterwater production production in in ZhangjiakouZhangjiakou and ChengdeChengde cities cities increased increased from from 15.60 15.60 × × 7 ofand 15and 16.8416.84 × 10× 10 m m in in 1995a 1995a toto 15.9415.94 × 10 10 m mandand 17.55 17.55 × × 10 10 m m in in 2005, 2005, and and then then decreased decreased toto 15.45 15.45 × × 10 10 m m andand 17.6017.60 ×× 10 10 m inin 2015.2015.

1995a1995a 2005a2005a 2015a2015a

Figure 4. Spatial–temporal distribution of water supply service in the Zhangcheng. FigureFigure 4. 4.Spatial–temporalSpatial–temporal distribution distribution of waterwater supplysupply service service in in the the Zhangcheng. Zhangcheng.

3.4. Distribution Characteristics of Water YieldYield in thethe ZhangchengZhangcheng DistrictDistrict byby RiverRiver BasinBasin 3.4. Distribution Characteristics of Water Yield in the Zhangcheng District by River Basin In 2014, 2014, General General Secretary Secretary Xi Xi repeatedly repeatedly mentioned mentioned that that during during the thecoordinated coordinated de- In 2014, General Secretary Xi repeatedly mentioned that during the coordinated de- developmentvelopment of ofBeijing, Beijing, Tianjin, Tianjin, and and Hebei, Hebei, in in or orderder to to ensure ensure national national water water security, security, it is velopmentnecessary toof strengthenBeijing, Tianjin, the development and Hebei, of in the or Zhangchengder to ensure water national conservation water security, area and it is necessarycomprehensively to strengthen repair the and development protect the water of the ecological Zhangcheng environment water conservation in the Zhangcheng area and comprehensivelyDistrict. TheThe vastvast repair majoritymajority and of of theprotect the Zhangcheng Zhangcheng the water District ecologicalDistrict belongs belongs environment to theto the Haihe Haihe in River the River Zhangcheng Basin Basin and District.hasand evidenthas The evident watershedvast watershedmajority connectivity. of connectivity. the Zhangcheng The average The average District water productionwater belongs production to in the different Haihein different watersheds River wa- Basin andintersheds thehas Zhangcheng evident in the Zhangcheng watershed District connectivity.District varies with varies time. Thewith Spatially,average time. Spatially, water the average productionthe average water water productionin different produc- iswa- tershedsmanifestedtion is manifested in the as Zhangcheng inland as inland river riverDistrict > Liaohe > Liaohe varies > capital > wi capitalth banktime. bank >Spatially, Yongding> Yongding the River averageRiver > > Daqing Daqing water Riverproduc-River tion(Figure is manifested5 5a).a). TheThe totaltotal as inland waterwater river productionproduction > Liaohe andand > thecapitalthe averageaverage bank water water> Yongding productionproduction River areare > Daqingsimilar similar Riverin in (Figuretime, andand 5a). thisthis The isis total spatiallyspatially water reﬂectedreflected production in in the the capital andcapital the management management average water industry industry production > > Yongding Yongding are similar River River > in time,Inland> Inland and River Riverthis >is > North spatially North Three Three reflected Rivers Rivers >in > Liaohe theLiaohe capital River River management > > Daqing Daqing River River industry Basin Basin (Figure (Figure> Yongding5b). 5b). River > Inland River > North Three Rivers > Liaohe River > Daqing River Basin (Figure 5b). a b a b

FigureFigure 5. AAverageverage (a)) andand TotalTotal annualannual ((bb)) waterwater supplysupply inin differentdifferent riverriver basinsbasins inin thethe ZhangchengZhangcheng District.District.

3.5. Water Yield Distribution Characteristics of Main Vegetation Types in the Zhangcheng District Figure 5. Average (a) and Total annual (b) water supply in different river basins in the Zhangcheng District. The vegetation classiﬁcation map of the research area was obtained from the Resource and Environmental Science and Data Center of the Chinese Academy of Sciences (https: //www.resdc.cn/1995,2005,2015, accessed on 12 August 2021). ArcGIS spatial analysis

was used to carry out zoning statistics on the water supply and service capabilities of various vegetation landscape types. The research areas were obtained in 1995. Twenty average (Figure6a) and total water supply (Figure6b) were obtained in the third phase of the three vegetation types in 2015. In 1995, the average water supply of each vegetation landscape was in the order: meadow > coniferous forest > other vegetation type > cultivated vegetation > grassland > shrub > grass > broadleaf forest. In 2005, the average water supply of vegetation landscapes was roughly similar to that of 1995. In 2015, coniferous forests had the largest average water supply across the vegetated landscape, followed by grassland and other vegetation types and cropland vegetation, while broadleaf forests remained the lowest. From the perspective of the total water supply, the cultivated landscape plays a leading role. The overall performance is as follows: the farmland ecosystems have the largest total water production, accounting for more than 49% of the total water supply; the Forests 2021, 12, x FOR PEER REVIEW 8 of 15

3.5. Water Yield Distribution Characteristics of Main Vegetation Types in the Zhangcheng Dis- trict The vegetation classification map of the research area was obtained from the Re- source and Environmental Science and Data Center of the Chinese Academy of Sciences (https://www.resdc.cn/1995,2005,2015, accessed on 12 August 2021). ArcGIS spatial analysis was used to carry out zoning statistics on the water supply and service capabilities of various vegetation landscape types. The research areas were obtained in 1995. Twenty average (Figure 6a) and total water supply (Figure 6b) were obtained in the third phase of the three vegetation types in 2015. In 1995, the average water supply of each vegetation landscape was in the order: meadow > coniferous forest > other vegetation type > cultivated vegetation > grassland > shrub > grass > broadleaf forest. In 2005, the average water supply of vegetation landscapes was roughly similar to that of 1995. In 2015, coniferous forests had the largest average water supply across the vegetated landscape, followed by grassland and other vegetation types and cropland vegetation, while broadleaf forests re- Forests 2021, 12, 1082 8 of 15 mained the lowest. From the perspective of the total water supply, the cultivated landscape plays a leading role. The overall performance is as follows: the farmland ecosystems have the largest total water production, accounting for more than 49% of the total water supply;thicket andthe grasslandsthicket and account grasslands for around account 30%, for and around coniferous 30%, and forests coniferous and other forests vegetation and othertypes’ vegetation contributions types’ are contributions relatively small are relati (Figurevely6b). small In the (Figure past 206b). years, In the the past coniferous 20 years, theforest, coniferous broadleaf forest, tree forest,broadleaf and meadowtree forest, water and supplymeadow services water havesupply shown services a trend have of showngrowth a followedtrend of growth by a decrease, followed with by a shrubs decrease, and with grasslands shrubs showingand grasslands an annual showing growth an annualtrend; thegrowth grasslands’ trend; the water grasslands’ source supply water has source declined supply annually. has declined annually.

a b

Figure 6. Twenty average (a) and total annual (b) water supply in different vegetation type areas in the Zhangcheng District. Figure 6. Twenty average (a) and total annual (b) water supply in different vegetation type areas in the Zhangcheng District. 3.6. The Inﬂuence of Topographic Factors on Water Yield in Zhangcheng District Topographic factors affecting water supply services in the Zhangcheng District were 3.6.analyzed The Influence from three of Topographic aspects: altitude, Factors on slope, Water and Yield slope in direction.Zhangcheng First District of all, according to the actualTopographic situation factors of the affecting study area water with supply a large se altitudervices in difference, the Zhangcheng steep peaks District and were high analyzedslopes, and from rolling three mountains, aspects: altitude, the elevation slope, an ofd theslope basin direction. was divided First of into all, sevenaccording levels: to <300,the actual 300~1500, situation 500~1000, of the study 1000~1500, area with 1500~2000, a large altitude 2000~2500, difference, and steep≥2500 peaks m. Researchand high slopes,shows thatand therolling average mountains, water production the elevation gradually of the decreases basin was with divided altitude into (Figure seven7 a);levels: the <300,total amount300~1500, of 500~1000, water resources 1000~1500, is spaced, 1500~2000, and 2000~2500, the total water and supply≥2500 m. in Research the river shows basin thatincreases the average with altitude; water production in areas above gradually 1500 m, decreases the water with supply altitude begins (Figure to rise with7a); the altitude. total amountThe regional of water water resources supply isis primarily spaced, and concentrated the total water in the altitudesupply in range the river of 500–1500 basin in- m, creasesaccounting with foraltitude; more thanin areas 70% above of the 1500 total m, water the water supply, supply while begins the total to rise water with supply altitude. in Forests 2021, 12, x FOR PEER REVIEWTheareas regional below 300 water m and supply above is 1500primarily m is relativelyconcentrated small in (Figure the altitude7b). Between range of 1995 500–1500 and 2015,9 of m, 15 accountingthe total amount for more of water than resources70% of the generally total water showed supply, a rising while trend the followedtotal water by supply a decline, in areasbut the below overall 300 change m and was above relatively 1500 m small. is relatively small (Figure 7b). Between 1995 and 2015, the total amount of water resources generally showed a rising trend followed by a decline,a but the overall change was relatively small. b

FigureFigure 7.7. TheThe distributiondistribution of of average average (a ()a and) and total total (b ()b water) water supply supply service service at differentat different elevations elevations in the in Zhangchengthe Zhangcheng District. Dis- trict. DEM was used to extract and grade the slopes in the research area and statistically analyzeDEM the was water used supply to extract distribution and grade in the the basin slopes at in different the research slopes area (Figure and8 ).statistically Between 1995analyze and the 2015, water spatially, supply the distribution average water in the production basin at indifferent the Zhangcheng slopes (Figure District 8). increased Between gradually1995 and 2015, with thespatially, increase the in average slopes. Inwater terms production of time, the in changingthe Zhangcheng trend is District consistent in- withincreased different gradually slopes, with the showing increase an in increasing slopes. In andterms decreasing of time, the trend. changing TheZhangcheng trend is con- ◦ District’ssistent within total waterdifferent supply slopes, is mainly showing concentrated an increasing in the and <15 decreasingslopes, accounting trend. The for Zhang- more ◦ thancheng 49% District’s of the watertotal water supply supply in the studyis mainly area. concentrated In the slope rangein the of<15° <5 slopes,, the water accounting supply infor the more basin than is relatively49% of the small. water The supply main in reason the study for this area. situation In the isslope closely range related of <5°, to thethe gridwater data supply of different in the basin slopes. is relatively small. The main reason for this situation is closely related to the grid data of different slopes.

a b

Figure 8. The distribution of average (a) and total (b) water supply service at different gradients of slopes in the Zhang- cheng District.

Figure 9 shows that the water output slopes of the Zhangcheng District are slightly different, but the overall water supply of the sunny slopes is slightly larger than that of the shady slopes. The average water supply volume of shady and sunny slopes is 43.35 and 43.63 mm, respectively, and the total water supply in the basin can be expressed as shady slope > sunny slope > half sunny slope > half shady slope. In terms of time, between 1995 and 2015, slopes generally showed a trend of slight growth before decreasing.

a b

Figure 9. The distribution of average (a) and total (b) water supply service for different slope aspects in the Zhangcheng District.

Forests 2021, 12, x FOR PEER REVIEW 9 of 15 Forests 2021, 12, x FOR PEER REVIEW 9 of 15

a b a b

Figure 7. The distribution of average (a) and total (b) water supply service at different elevations in the Zhangcheng Dis- Figuretrict. 7. The distribution of average (a) and total (b) water supply service at different elevations in the Zhangcheng Dis- trict. DEM was used to extract and grade the slopes in the research area and statistically analyzeDEM the was water used supply to extract distribution and grade in the the ba slopessin at in different the research slopes area (Figure and 8).statistically Between analyze1995 and the 2015, water spatially, supply distributionthe average inwater the baproductionsin at different in the slopes Zhangcheng (Figure 8).District Between in- 1995creased and gradually 2015, spatially, with the the increase average in slopes.water productionIn terms of time,in the the Zhangcheng changing trend District is con- in- creasedsistent within gradually different with theslopes, increase showing in slopes. an increasing In terms andof time, decreasing the changing trend. trend The Zhang- is con- sistentcheng District’swithin different total water slopes, supply showing is mainly an increasing concentrated and decreasingin the <15° slopes,trend. The accounting Zhang- chengfor more District’s than 49% total of water the water supply supply is mainly in the concentrated study area. inIn thethe <15°slope slopes, range accountingof <5°, the forwater more supply than in 49% the ofbasin the iswater relatively supply small. in the The study main area. reason In thefor slopethis situation range of is <5°, closely the Forests 2021, 12, 1082 9 of 15 waterrelated supply to the gridin the data basin of differentis relatively slopes. small. The main reason for this situation is closely related to the grid data of different slopes. a b a b

Figure 8. The distribution of average (a) and total (b) water supply service at different gradients of slopes in the Zhang- FigurechengFigure District. 8. The 8. The distribution distribution of average of average (a) and (a) andtotal total (b) water (b) water supply supply service service at different at different gradients gradients of slopes of slopes in the in Zhang- the chengZhangcheng District. District. Figure 9 shows that the water output slopes of the Zhangcheng District are slightly Figure9 shows that the water output slopes of the Zhangcheng District are slightly different,different,Figure but but 9 shows the overalloverall that water thewater water supply supply output of of the the slopes sunny sunny slopesof theslopes isZhangcheng slightly is slightly larger District larger than that thanare of slightly that the of different,theshady shady slopes. but slopes. the The overallThe average average water water watersupply supply supply of volume the volumesu ofnny shady slopes of shady and is sunnyslightly and sunny slopes larger isslopes 43.35than is andthat 43.35 of theand43.63 shady 43.63 mm, mm,slopes. respectively, respectively, The average and the and water total the water totalsupply supplywater volume supply in the ofbasin shadyin the can basinand be expressedsunny can be slopes expressed as shady is 43.35 as andshadyslope 43.63 slope > sunny mm, > sunny sloperespectively, >slope half > sunny half and sunny slopethe total > slope half water shady> half supply slope.shady in Inslope. the terms basin In of terms time, can of betweenbe time, expressed between 1995 as shady1995and and 2015, slope 2015, slopes > sunny slopes generally slope generally > showed half showedsunny a trend slope a oftrend slight> half of growth slightshady growth slope. before In decreasing.before terms decreasing. of time, between 1995 and 2015, slopes generally showed a trend of slight growth before decreasing. a b a b

FigureFigure 9. 9.TheThe distribution distribution of averageaverage (a ()a and) and total total (b) ( waterb) water supply supply service service for different for different slope aspects slope in aspects the Zhangcheng in the Zhangcheng District. District. Figure 9. The distribution of 3.7.average Analysis (a) and of Driverstotal (b) of water Change supply in Water service Production for different slope aspects in the Zhangcheng District. The impact of climate change on water production in the Zhangcheng District draws a correlation between the depth of water production, precipitation, and evaporation (Figure 10). Over the years, the average depth of water production has been positively correlated with the average precipitation. The potential evaporation emission is negatively correlated, consistent with Li Yiying, Yang Ying, Li Yingying, Wang Culting, and Han Dongxue, and contrary to Gong Shihan. The research conclusions of a positive correlation between water source conservation and evaporation emission are biased. The changing trend of average water production depth and precipitation in this study is the same. The years in which the extremes occur correspond to precipitation extremes, but there are signiﬁcant deviations from the potential evapotranspiration emission trends, indicating that precipitation is the main factor inﬂuencing water production. Forests 2021, 12, x FOR PEER REVIEW 10 of 15

3.7. Analysis of Drivers of Change in Water Production The impact of climate change on water production in the Zhangcheng District draws a correlation between the depth of water production, precipitation, and evaporation (Fig- ure 10). Over the years, the average depth of water production has been positively correlated with the average precipitation. The potential evaporation emission is negatively correlated, consistent with Li Yiying, Yang Ying, Li Yingying, Wang Culting, and Han Dongxue, and contrary to Gong Shihan. The research conclusions of a positive correlation between water source conservation and evaporation emission are biased. The changing trend of average water production depth and precipitation in this study is the same. The years in which the extremes occur correspond to precipitation extremes, but there are sig- Forests 2021, 12, 1082 nificant deviations from the potential evapotranspiration emission trends, indicating10 that of 15 precipitation is the main factor influencing water production.

Figure 10. Correlations of annual average water yield with precipitation and potential evapotranspiration in the Figure 10. Correlations of annual average water yield with precipitation and potential evapotranspiration in the Zhang- chengZhangcheng District. District. 3.8. The Influence of Topographic Factors on Water Production in the Zhangcheng District 3.8. The Influence of Topographic Factors on Water Production in the Zhangcheng District A correlation between water production depth and different altitudes and slopes was establishedA correlation (Figure between 11). In water the range production of 0–1200 dept m,h theand average different water altitudes production and slopes depth was is establishedsignificantly (Figure negatively 11). In correlated the range withof 0–120 altitude0 m, (ther = average−0.0903, waterR2 = 0.9528);production in the depth range is significantlyof >1300 m, negatively there is anegative correlated correlation with altitude with ( altituder= −0.0903, (r = −=0.0173, 0.9528);R in2 = the 0.8262), range butof >1300the trend m, there is relatively is a negative flat. correlation Surface runoff with has altitude a cumulative (r= −0.0173, effect = in 0.8262), the area, but which the trend has isgreat relatively potential flat. for Surface runoff runoff formation, has a cumulative so the water effect production in the area, volume which change has great is negatively poten- tialrelated for runoff to altitude. formation, The correlation so the water between produc slopetion volume and water change yield is changenegatively is the related same to as altitude.that of elevation. The correlation In a range between lower slope than and 25◦ ,wate the averager yield change water productionis the same isas significantly that of ele- ◦ Forests 2021, 12, x FOR PEER REVIEWvation.negatively In a correlatedrange lower with than the 25°, slope the (averager = −9.8983, waterR 2production= 0.9352); inis asignificantly range greater negatively than11 25of 15 , 2 correlatedthe average with water the production slope (r = − negatively9.8983, correlates= 0.9352); in with a range the slope grea (terr = than−0.9552, 25°, Rthe= average 0.9932), waterand the production trend is relatively negatively smooth. correlates with the slope (r = −0.9552, = 0.9932), and the trend is relatively smooth. a b

FigureFigure 11. CorrelationsCorrelations of of annual annual average average water water yield yield with with different different elevations elevations (a) and (a) gradients and gradients of slopes of slopes(b) in the (b) Zhang- in the Zhangchengcheng District. District.

3.9. The Impact of Land Use Change on Water Production in Zhangcheng District Land use is the most critical data source of the InVEST water production model and one of the key factors affecting water production. Table 2 shows noticeable differences in yearly water production between 1995 and 2015, which may be caused by different regional geographical differences, consistent with the results of [35,43], such as in the Zhangjiakou-Schengde region [38] and Shiyang River basin. Statistics on the various land use changes caused over the years, their contribution to water production and conservation, and water production and conservation changes are presented in Table 2. The overall land use change from 1995 to 2015 is as follows: construction land, sparse forest land, grassland, shrubs, woodland, cultivated land. As a result, the water production in construction land and cultivated land has been reduced. Although the area is large, due to the low conservation capacity of construction land and unused land water sources, the contribution to water production is still small. The main reason for the decrease in the overall area of grassland and the increase in water production may be the overall increase in water production due to the increase in regional precipitation over the years. Moreover, the dynamic change in unused land in Zhangjiakou over the years—that is, the unused land area in areas with less precipitation, such as Kangbao and Guyuan—and the decrease in Huailai might influence this decrease. Unused land increases in areas with more water, so areas with more precipitation produce more water than areas with less precipitation. In terms of water production, the most productive areas are cultivated land and grassland, followed by shrubs, construction land, and woodland. Due to the small amount of precipitation in the Zhangjiakou area, the evaporation and emission of forest land are too large, thus reducing water production.

Table 2. Changes in water yield caused by various land uses in Zhangcheng District over several years.

Water Yield Contribution (%) Variation (%) Type 1995a 2005a 2015a Area/km2 Water Yield/(×108 m³) Farmland 50.84 54.36 51.38 −7.48 −2.99

Forest 4.79 2.82 2.78 10.02 40.84

Shrub 9.26 4.98 4.13 11.94 54.55

Sparse forest 2.50 0.62 0.53 73.50 78.55

Grassland 23.03 23.20 21.90 −23.37 3.07

Forests 2021, 12, 1082 11 of 15

3.9. The Impact of Land Use Change on Water Production in Zhangcheng District Land use is the most critical data source of the InVEST water production model and one of the key factors affecting water production. Table2 shows noticeable differences in yearly water production between 1995 and 2015, which may be caused by different regional geographical differences, consistent with the results of [35,43], such as in the Zhangjiakou- Schengde region [38] and Shiyang River basin. Statistics on the various land use changes caused over the years, their contribution to water production and conservation, and water production and conservation changes are presented in Table2. The overall land use change from 1995 to 2015 is as follows: construction land, sparse forest land, grassland, shrubs, woodland, cultivated land. As a result, the water production in construction land and cultivated land has been reduced. Although the area is large, due to the low conservation capacity of construction land and unused land water sources, the contribution to water production is still small. The main reason for the decrease in the overall area of grassland and the increase in water production may be the overall increase in water production due to the increase in regional precipitation over the years. Moreover, the dynamic change in unused land in Zhangjiakou over the years—that is, the unused land area in areas with less precipitation, such as Kangbao and Guyuan—and the decrease in Huailai might inﬂuence this decrease. Unused land increases in areas with more water, so areas with more precipitation produce more water than areas with less precipitation. In terms of water production, the most productive areas are cultivated land and grassland, followed by shrubs, construction land, and woodland. Due to the small amount of precipitation in the Zhangjiakou area, the evaporation and emission of forest land are too large, thus reducing water production.

Table 2. Changes in water yield caused by various land uses in Zhangcheng District over several years.

Water Yield Contribution (%) Variation (%) Type 1995a 2005a 2015a Area/km2 Water Yield/(×108 m3) Farmland 50.84 54.36 51.38 −7.48 −2.99 Forest 4.79 2.82 2.78 10.02 40.84 Shrub 9.26 4.98 4.13 11.94 54.55 Sparse forest 2.50 0.62 0.53 73.50 78.55 Grassland 23.03 23.20 21.90 −23.37 3.07 Construction land 5.64 5.17 12.29 −105.70 −122.00 Unutilized land 3.94 8.84 7.00 −73.31 −81.04

4. Discussion 1. Between 1995 and 2015, the water supply service in the Zhangcheng District showed a trend of ﬁrst increasing and then slightly decreasing, and the distribution pattern showed minor changes. This phenomenon is related to watershed meteorological factors (such as precipitation and potential evaporation) and the distribution area of the vegetation distribution pattern from a vegetation landscape type. Precipitation in the watershed of the Zhangcheng District is the primary source of ecosystem water circulation, and potential evaporation indirectly reﬂects the water consumption capacity of regional ecosystems [35,42]; the bottom surface state and its spatial distribution also affect the distribution pattern of the water supply capacity of watershed ecosystems [44]. Regarding spatial distribution, areas with a high water supply in the Zhangcheng District are mainly distributed in mountainous forest areas with abundant rainfall and lush forest growth, such as Fengning Manchu Autonomous Region, Longhua County, and Waichang County, located in the Yanshan-Taihang Mountains. Although these areas have relatively high rainfall, the air is relatively humid. Coniferous forests have low evapotranspiration and high water production. When old coniferous forests are cut, planted forests and secondary forests do not proliferate, and the water production volume in river basins increases. However, Forests 2021, 12, 1082 12 of 15

over time, vegetation growth and restoration entered a mixed growth stage involving shrubs, secondary broadleaf forests, mixed coniferous forests, artificial spruce forests, a forest cover increase, and a water production decline [45–47]. Under the same cli- matic background, the water supply in the river basin decreased with the restoration of vegetation and the expansion of the proportion of forest land. This phenomenon and its distribution pattern are similar to those in areas such as bridge reservoirs [48], the upper reaches of Miyun reservoirs [49,50], the Lancang River basin [51], or water supply distribution patterns. However, the distribution of the parallel area of the Three Rivers [52] is slightly different, mainly manifested in ice and snow glaciers. This is mainly because the parallel area of the Three Rivers belongs to the high-altitude zone, and the ice and snow cover is extensive, so its water production is high. The Zhangcheng District is relatively unaffected by ice and snow glaciers and has primarily seasonal snow accumulation produced in the basin. The influence of the water process is relatively weak. In addition, the ability of the ecosystem to intercept rainfall is weak, the root system is shallow, and the cultivated area is large, so the total supply of farmland water is relatively large. 2. Among different topographic factors, the average water production in the Zhangcheng District decreases with the increase of altitude and slope, and the water supply to the shadowed slope is greater than that of the sunny slope. This is similar to the results of other scholars [53] and is mainly influenced by the characteristics of rainfall and topographic differences. The highest precipitation is found at elevations of 500–1500 m. In the windward slope area, the forest is widely distributed, the topographic rain characteristics are apparent, and the potential evaporation is not large. For example, there are scattered trees such as deciduous broad-green broadleaf forests and broadleaf mixed forests, and the forest water source has a strong conservation capacity, so the water supply is large. In Kangbao, Zhangbei, Shangyi, and other places in the plateau area of the dam, in addition to cultivated land, there are also industrial and mining lands, residential land, and other construction lands. Because the total area is minimal, the total water supply is relatively small. At the same time, these areas have crossed the forest line of most forest vegetation, and the surface vegetation landscape has gradually been irrigated with grassland and cold grassland. Alpine sparse vegetation and bare rock are replaced by relatively little rainfall and the weak conservation capacity of vegetation sources, so its water supply is relatively small.

5. Conclusions 1. In the Zhangcheng District ecosystem, the average water supply is approximately 43.5 mm, which shows a certain regularity in space. The high-value areas are mainly distributed in the mountain forest areas, with the most prominent water conservation forests in the dams of Yanshan-Tahang Mountain. Most low-value areas are concentrated in the upper plains or altitudes of dams with low rainfall and frequent human activities. From the perspective of land use type, the water production capacity of the farmland ecosystem in the Zhangcheng District is relatively high. In terms of time, the water supply services in the basin show a trend of initial growth and then a slight decrease. 2. The overall water supply in the Zhangcheng District tends to rise first and then decrease with the altitude increase. The water supply in the areas with steep slopes is slightly higher than in areas with mild slopes, and the high-value areas appear at 500–1500 m and 300–500◦, respectively; the water supply volume of Yin and Yangpo is greater than that of the half-yang slope and half-yin slopes. 3. The introduction of the InVEST model provides a feasible method for estimating the spatial distribution of water supply services in large- and medium-scale regions. However, there may be uncertainties in the study results due to the simplified model structure and methodology and the lack of large field stations and long-term experi- mental observation data in the study area. Qualitatively, it is suggested that in future Forests 2021, 12, 1082 13 of 15

research, based on the evaluation model and its parameter suitability, the observation, localization, and veriﬁcation of ﬁeld data should be further strengthened, focusing on developing China’s localized evaluation model to ensure the credibility and reliability of the evaluation results.

Author Contributions: Conceptualization, R.L. and B.W.; methodology, R.L.; software, R.L.; validation B.W., X.N. and Q.S.; formal analysis, R.L.; investigation, R.L; resources, Q.S. and R.L.; data curation, Q.S.; writing—original draft preparation, R.L.; writing—review and editing, R.L.; B.W., X.N.; visualization, R.L.; supervision, X.N. and Q.S.; project administration, X.N.; funding acquisition, X.N. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the Central Non-profit Research Institution of CAF, grant number CAFYBB2020ZE003 and CAFYBB2020ZD002-2; Ecological positioning observation and ecological function calculation of national public welfare forest construction effectiveness monitoring and evaluation, grant number 2130207-20-201/107. Conflicts of Interest: The authors declare no conflict of interest.

References 1. Li, M.; Liang, D.; Xia, J.; Song, J.; Cheng, D.; Wu, J.; Cao, Y.; Sun, H.; Li, Q. Evaluation of water conservation function of Danjiang River Basin in Qinling Mountains, China based on InVEST model. J. Environ. Manag. 2021, 286, 112–212. [CrossRef] 2. Li, X.; Niu, J.; Xie, B. Study on hydrological functions of litter layers in North China. PLoS ONE 2013, 8, e70328. [CrossRef] 3. Du, J.; Niu, J.Z.; Gao, Z.L.; Chen, X.W.; Zhang, L.; Li, X.; van Doorn, N.S.; Luo, Z.T.; Zhu, Z.J. Effects of rainfall intensity and slope on interception and precipitation partitioning by forest litter layer. Catena 2019, 172, 711–718. [CrossRef] 4. Biao, Z.; Wenhua, L.; Gaodi, X.; Yu, X. Water conservation of forest ecosystem in Beijing and its value. Ecol. Econ. 2010, 69, 1416–1426. [CrossRef] 5. Zhu, H.; Wang, G.; Yinglan, A.; Liu, T. Ecohydrological effects of litter cover on the hillslope-scale infiltration-runoff patterns for layered soil in forest ecosystem. Ecol. Eng. 2020, 155, 105930. [CrossRef] 6. Fischer, J.; Lindenmayer, D.B.; Manning, A.D. Biodiversity, ecosystem function, and resilience: Ten guiding principles for commodity production landscapes. Front. Ecol. Environ. 2006, 4, 80–86. [CrossRef] 7. Snelgrove, P.V. Getting to the bottom of marine biodiversity: Sedimentary habitats: Ocean bottoms are the most widespread habitat on earth and support high biodiversity and key ecosystem services. Bio-Science 1999, 49, 129–138. 8. Long, H.; Tang, G.; Li, X.; Heilig, G.K. Socio-economic driving forces of land-use change in Kun-shan, the Yangtze River Delta economic area of China. J. Environ. Manag. 2007, 83, 351–364. [CrossRef] 9. Jiang, Y. China’s water scarcity. J. Environ. Manag. 2009, 90, 3185–3196. [CrossRef] 10. Varis, O.; Vakkilainen, P. China’s 8 challenges to water resources management in the first quarter of the 21st Century. Geomorphology 2001, 41, 93–104. [CrossRef] 11. Wealands, S.R.; Grayson, R.B.; Walker, J.P. Quantitative comparison of spatial fields for hydro-logical model assessment—-some promising approaches. Adv. Water Resour. 2005, 28, 15–32. [CrossRef] 12. Larsen, L.G.; Choi, J.; Nungesser, M.K.; Arvey, J.W. Directional connectivity in hydrology and ecology. Ecol. Appl. 2012, 22, 2204–2220. [CrossRef] 13. Hoyer, R.; Chang, H. Assessment of freshwater ecosystem services in the Tualatin and Yamhill basins under climate change and urbanization. Appl. Geogr. 2014, 53, 402–416. [CrossRef] 14. Hargrove, W.W.; Hoffman, F.M. Potential of multivariate quantitative methods for delineation and visualization of ecoregions. Environ. Manag. 2004, 34, S39–S60. [CrossRef] 15. Golmohammadi, G.; Prasher, S.; Madani, A.; Rudra, R. Evaluating three hydrological distributed watershed models: MIKE-SHE, APEX, SWAT. Hydrology 2014, 1, 20–39. [CrossRef] 16. Chen, S.; Wen, Z.; Jiang, H.; Zhao, Q.; Zhang, X.; Chen, Y. Temperature vegetation dryness index estimation of soil moisture under different tree species. Sustainability 2015, 7, 11401–11417. [CrossRef] 17. Neitsch, S.L.; Arnold, J.G.; Kiniry, J.R.; Williams, J.R. Soil and Water Assessment Tool Theoretical Documentation Version 2009; Texas Water Resources Institute: College Station, TX, USA, 2011. 18. Mishra, S.K.; Singh, V.P. Soil Conservation Service Curve Number (SCS-CN) Methodology; Springer Science & Business Media: Berlin/Heidelberg, Germany, 2013; Volume 42. 19. Guerry, A.D.; Ruckelshaus, M.H.; Arkema, K.K.; Bernhardt, J.R.; Guannel, G.; Kim, C.K.; Marsik, M.; Papenfus, M.; Verutes, G.; Beck, M.; et al. Modeling benefits from nature: Using ecosystem services to inform coastal and marine spatial planning. Int. J. Biodivers. Sci. Ecosyst. Serv. Manag. 2012, 8, 107–121. [CrossRef] 20. De Groot, R.S.; Alkemade, R.; Braat, L.; Hein, L.; Willemen, L. Challenges in integrating the con-cept of ecosystem services and values in landscape planning, management and decision making. Ecol. Complex. 2010, 7, 260–272. [CrossRef] Forests 2021, 12, 1082 14 of 15

21. Ouyang, Z.; Zheng, H.; Xiao, Y.; Polasky, S.; Liu, J.; Xu, W.; Daily, G.C. Improvements in ecosys-tem services from investments in natural capital. Science 2016, 352, 1455–1459. [CrossRef] 22. Tallis, H.T.; Ricketts, T.; Nelson, E.; Wolny, S.; Olwero, N.; Vigerstol, K.; Pennington, D.; Mendoza, G.; Aukema, J.; Foster, J.; et al. InVEST 2.5.4 User’ s Guide; The Natural Capital Project: Stanford, CA, USA, 2013. 23. Ismail, M.S.; Moghavvemi, M.; Mahlia, T.M.I. Characterization of PV panel and global optimi-zation of its model parameters using genetic algorithm. Energy Convers. Manag. 2013, 73, 10–25. [CrossRef] 24. Schulp, C.J.; Lautenbach, S.; Verburg, P.H. Quantifying and mapping ecosystem services: De-mand and supply of pollination in the European Union. Ecol. Indic. 2014, 36, 131–141. [CrossRef] 25. Goldstein, J.H.; Caldarone, G.; Duarte, T.K.; Ennaanay, D.; Hannahs, N.; Mendoza, G.; Polasky, S.; Wolny, S.; Daily, G.C. Inte-grating ecosystem-service tradeoffs into land-use decisions. Proc. Natl. Acad. Sci. USA 2012, 109, 7565–7570. [CrossRef] 26. Bagstad, K.J.; Semmens, D.J.; Winthrop, R. Comparing approaches to spatially explicit ecosystem service modeling: A case study from the San Pedro River, Arizona. Ecosyst. Serv. 2013, 5, 40–50. [CrossRef] 27. Li, S.; Gu, S.; Liu, W.; Han, H.; Zhang, Q. Water quality in relation to land use and land cover in the upper Han River Basin, China. Catena 2008, 75, 216–222. [CrossRef] 28. Lü, L.; Ren, T.; Sun, C.; Zheng, D.; Wang, H. Spatial and temporal changes of water supply and water conservation function in Sanjiangyuan National Park from 1980 to 2016. Acta Ecol. Sin. 2020, 40, 993–1003. 29. Arnold, J.G. Spatial Scale Variability in Model Development and Parameterization. Ph.D. Thesis, Purdue University, West Lafayette, IN, USA, 1992. 30. Duan, L.; Huang, M.; Zhang, L. Differences in hydrological responses for different vegetation types on a steep slope on the Loess Plateau, China. J. Hydrol. 2016, 537, 356–366. [CrossRef] 31. Redhead, J.W.; Stratford, C.; Sharps, K.; Jones, L.; Ziv, G.; Clarke, D.; Bullock, J.M. Empirical validation of the InVEST water yield ecosystem service model at a national scale. Sci. Total Environ. 2016, 569, 1418–1426. [CrossRef][PubMed] 32. Hamel, P.; Guswa, A.J. Uncertainty analysis of a spatially explicit annual water-balance model: Case study of the Cape Fear basin, North Carolina. Hydrol. Earth Syst. Sci. 2015, 19, 839–853. 33. Zhang, L.; Dawes, W.R.; Walker, G.R. Response of mean annual evapotranspiration to vegetation changes at catchment scale. Water Resour. Res. 2001, 37, 701–708. [CrossRef] 34. Leh, M.D.; Matlock, M.D.; Cummings, E.C.; Nalley, L.L. Quantifying and mapping multiple ecosystem services change in West Africa. Agric. Ecosyst. Environ. 2013, 165, 6–18. [CrossRef] 35. Francesconi, W.; Srinivasan, R.; Pérez-Miñana, E.; Willcock, S.P.; Quintero, M. Using the Soil and Water Assessment Tool (SWAT) to model ecosystem services: A systematic review. J. Hydrol. 2016, 535, 625–636. [CrossRef] 36. Fisher, B.; Turner, R.K.; Burgess, N.D.; Swetnam, R.D.; Green, J.; Green, R.E.; Kajembe, G.; Kulindwa, K.; Lewis, S.L.; Marchant, R.; et al. Measuring, modeling and mapping ecosystem services in the Eastern Arc Mountains of Tanzania. Prog. Phys. Geogr. 2011, 35, 595–611. [CrossRef] 37. Donohue, R.J.; Roderick, M.L.; McVicar, T.R. Roots, storms and soil pores: Incorporating key ecohydrological processes into Budyko’s hydrological model. J. Hydrol. 2012, 436, 35–50. [CrossRef] 38. Gupta, S.; Larson, W.E. Estimating soil water retention characteristics from particle size distribu-tion, organic matter percent, and bulk density. Water Resour. Res. 1979, 15, 1633–1635. [CrossRef] 39. Hargreaves, G.H.; Samani, Z.A. Estimating potential evapotranspiration. J. Irrig. Drain. Div. 1982, 108, 225–230. [CrossRef] 40. Hamon, W.R. Estimating potential evapotranspiration. Trans. Am. Soc. Civ. Eng. 1963, 128, 324–338. [CrossRef] 41. Canadell, J.; Jackson, R.B.; Ehleringer, J.B.; Mooney, H.A.; Sala, O.E.; Schulze, E.D. Maximum rooting depth of vegetation types at the global scale. Oecologia 1996, 108, 583–595. [CrossRef][PubMed] 42. Xiao, R.B.; Ouyang, Z.Y.; Zheng, H.; Li, W.F.; Schienke, E.W.; Wang, X.K. Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing, China. J. Environ. Sci. 2007, 19, 250–256. [CrossRef] 43. Allen, R.G.; Pereira, L.S.; Raes, D.; Smith, M. Crop Evapotranspiration-Guidelines for Computing Crop Water Requirements-FAO Irrigation and Drainage Paper 56; FAO: Rome, Italy, 1998; Volume 300, p. D05109. 44. Wang, Y.; Xiao, H.L.; Lu, M.F. Analysis of water consumption using a regional input–output model: Model development and application to Zhangye City, Northwestern China. J. Arid Environ. 2009, 73, 894–900. [CrossRef] 45. Zhang, Y.; Liu, S.; Gu, F. The impact of forest vegetation change on water yield in the subalpine region of southwestern China. Acta Ecol. Sin. 2011, 31, 7601–7608. 46. Bosch, J.M.; Hewlett, J.D. A review of catchment experiments to determine the effect of vege-tation changes on water yield and evapotranspiration. J. Hydrol. 1982, 55, 3–23. [CrossRef] 47. Hibbert, A.R. Forest Treatment Effects on Water Yield; Coweeta Hydrologic Laboratory, Coweeta Hydrologic Laboratory, Southeast- ern Forest Experiment Station: Asheville, NC, USA, 1965. 48. Sun, Y.; Li, J.; Ma, R.; Li, W. Style of spatial distribution of water supply service in Yuqiao watershed. J. Water Resour. Water Eng. 2015, 6.[CrossRef] 49. Wang, F.; Zheng, H.; Wang, X.; Peng, W.; Ma, D.; Li, C. Classiﬁcation of the relationship between household welfare and ecosystem reliance in the Miyun Reservoir Watershed, China. Sustainability 2017, 9, 2290. [CrossRef] 50. Lang, X. Impacts of Different Forest Watershed Composition Factors on Soil Condition in Upstream of Miyun Reservoir Watershed, Nothern China and Its Current Situation. Ph.D. Thesis, Lakehead University, Thunder Bay, ON, Canada, 2020. Forests 2021, 12, 1082 15 of 15

51. Long, C.; Gaodi, X.; Changshun, Z.; Sha, P.; Na, F.; Liqiang, G.; Caixia, Z. Modelling ecosystem water supply services across the Lancang River Basin. J. Resour. Ecol. 2011, 2, 322–327. 52. Lin, S.; Wu, R. The spatial pattern of water supply ecosystem service in the Three Parallel Rivers Region. J. West China For. Sci. 2015, 44, 8–15. 53. Canqiang, Z.; Wenhua, L.; Biao, Z.; Moucheng, L. Water yield of Xitiaoxi river basin based on InVEST modeling. J. Resour. Ecol. 2012, 3, 50–54. [CrossRef]