# A Sustainable Land Utilization Pattern for Confirming Integrity of Economic and Ecological Objectives under Uncertainties

^{1}

^{2}

^{3}

^{4}

^{5}

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Application

#### 2.1. Study Area

^{2}. The study region is composed of 65% mountain area and 35% flat depression. Since it is situated in the transition zone between the northern subtropical region and the warm temperate zone, the area is suitable for crop plantation with the average annual precipitation being 645 mm. In the study region, endemic plants such as Taxodium, Ginko and Metasequoia grow well to support regional wood-processing industry. Meanwhile, irrigation for crops such as grains, oil plants, vegetables and fruits has been developed rapidly in recent years, which can improve the quality of human living in the study region.

^{3}km

^{2}, while water deficit of irrigating was 38.13 × 10

^{6}m

^{3}at its peak [30,31,32,33]. Meanwhile, excessive fertilization can aggravate severe soil loss and pollution emission, leading to the destruction of land function.

#### 2.2. Construction of an Integrated Crop–Forest System

#### 2.3. Modeling Formulation

- Reallocated land resource with market approach:$$\sum _{t=1}^{3}{\displaystyle \sum _{m=1}^{3}WR{A}_{tm}}}+{\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{n=1}^{3}WR{E}_{tn}}}\le T{A}_{t$$In a traditional land utilization plan, the actual land resources can be reallocated to each plant by the proportion based on expected target. The market approach can be introduced to prompt land resources from lower value to higher value by the law of value, which can support land reallocation optimally. Model (2a) shows land resources reallocation based on market approach, where the productivities of land resources can be improved by reallocated actions ($WR{A}_{tm}$ and $WR{E}_{tn}$) based on total land resources ($T{A}_{t}$) (ha). $T{A}_{t}$ is the total land resources in study region (ha).
- Water quantity and water supply capacity for irrigative activities:$$\begin{array}{l}Cr\{[{\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{m=1}^{3}(W{M}_{tm}}}-S{M}_{tm})\times {\mathsf{\alpha}}_{tm}+{\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{n=1}^{3}(WE{A}_{tn}-}}SE{A}_{tn})\times {\mathsf{\beta}}_{tn}]\le [({\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{p=1}^{5}{\tilde{QF}}_{tp}}}+{\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{p=1}^{5}{\tilde{QG}}_{tp})}}-{E}_{tp}-\\ {\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{n=1}^{3}(1-{\mathsf{\beta}}_{tn})\times WR{E}_{tn}}}\times RE{C}_{tn}\times R{O}_{tn}-{H}_{tp}]\}\ge \mathsf{\mu}\end{array}$$$$Cr\{[({\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{p=1}^{5}{\tilde{QF}}_{tp}}}+{\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{p=1}^{5}{\tilde{QG}}_{tp})}}-{E}_{tp}-{\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{n=1}^{3}(1-{\mathsf{\beta}}_{tn})\times WR{E}_{tn}}}\times RE{C}_{tn}\times R{O}_{tn}-{H}_{tp}]\ge CS{M}_{tp}^{}\}\ge \mathsf{\mu}$$$$\begin{array}{l}Cr\{[{\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{m=1}^{3}(WR{A}_{tm}}}-SR{A}_{tm})\times {\mathsf{\alpha}}_{tm}+{\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{n=1}^{3}(WR{E}_{tn}-}}SR{E}_{tn})\times {\mathsf{\beta}}_{tn}]\le [({\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{p=1}^{5}{\tilde{QF}}_{tp}}}+{\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{p=1}^{5}{\tilde{QG}}_{tp})}}-{E}_{tp}-\\ {\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{n=1}^{3}(1-{\mathsf{\beta}}_{tn})\times WR{E}_{tn}}}\times RE{C}_{tn}\times R{O}_{tn}-{H}_{tp}]\}\ge \mathsf{\mu}\end{array}$$Model (2b) presents available water for irrigation and forest without market approach, where a land plan associated with water quantity based on regional water resource load can be expressed. If water cannot satisfy the expected land targets, water deficits occur, which are caused by uncertain water availabilities. Water availability equals available water from surface and underground (${QF}_{tp}$ and ${QG}_{tp}$) minus evaporation (${E}_{tp}$), watercourse loss (${H}_{tp}$) and minimum ecological requirement ($\sum _{t=1}^{3}{\displaystyle \sum _{n=1}^{3}(1-{\mathsf{\beta}}_{tn})\times WR{E}_{tn}}}\times RE{C}_{tn}\times R{O}_{tn$) (m
^{3}). ${QF}_{tp}$ is the available water from surface (m^{3}); ${QG}_{tp}$ is the available water from underground (m^{3}); ${E}_{tp}$ is the total evaporation in study region (m^{3}); ${H}_{tp}$ is the watercourse loss (m^{3}); $RE{C}_{t}$ is water conservation ability of forest per ha (m^{3}/ha); and $R{O}_{t}$ is rainfall runoff coefficient (%). In Model (6b), since available water can be deemed as stochastic and random variables impacted by spatio-temporal factors, fuzzy measure Cr can be advocated to express such fuzziness, where $\mathsf{\mu}$ is the credibility level through the QSF method (as shown in the Appendix A). Model (2c) shows the water supply capacity for irrigative activities in period t under probability ${p}_{tp}$ (m^{3}). The model presents that maximum supply capacity (i.e., $CS{M}_{tp}^{}$) can be restricted by water availability. A market approach can prompt the efficiency of land plan; limited water resources can restrict the development of crop planting and environmental protecting. Thus, Model (2d) presents available water for irrigation and forest protection through a market approach, where water deficits occur when water cannot be delivered to the reallocated land. $SR{A}_{tm}^{}$ and $SR{E}_{tn}^{}$ are the water shortage area (ha). - Pollution purification capacity through market approach:$$\sum _{t=1}^{3}{\displaystyle \sum _{m=1}^{3}(D{A}_{tm}^{N}+D{A}_{tm}^{P})\le (N{P}_{t}+N{N}_{t}}})\times {\displaystyle \sum _{p=1}^{5}{p}_{tp}}\times [{\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{m=1}^{3}(WR{E}_{tn}}}-SR{E}_{tn})]$$
- Total nitrogen allowance:$$Cr\{{\displaystyle \sum _{p=1}^{5}{p}_{tp}\times [}{\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{m=1}^{3}C{A}_{tm}^{N}\times (WR{A}_{tm}}}-SR{A}_{tm})\times s{l}_{tm}^{}\times E{N}_{tm}^{N}]\cdot (1-N{N}_{t}^{})\le {\tilde{TNP}}_{tp}^{}\times (1-tp{n}_{t}^{})\}\ge \mathsf{\mu}$$
- Total phosphorus allowance:$$Cr\{{\displaystyle \sum _{p=1}^{5}{p}_{tp}\times [}{\displaystyle \sum _{t=1}^{3}{\displaystyle \sum _{m=1}^{3}C{A}_{tm}^{P}\times (WR{A}_{tm}}}-SR{A}_{tm})\times s{l}_{tm}\times E{P}_{tm}^{P}]\times (1-N{P}_{t}^{})\le {\tilde{TPP}}_{tp}^{}\times (1-tp{p}_{t}^{})\}\ge \mathsf{\mu}$$
- Soil and water conservation capacity:$$\sum _{t=1}^{3}{\displaystyle \sum _{m=1}^{3}LM{S}_{tm}^{}\times (WR{A}_{tm}}}-SR{A}_{tm})\times sl\le LW{T}_{tm$$$$\sum _{t=1}^{3}{\displaystyle \sum _{m=1}^{3}LM{W}_{tm}^{}\times (WR{A}_{tm}}}-SR{A}_{tm})\times w{r}_{t}\le LS{T}_{t$$Model (2e) presents that capacity of purification from forest system (through ecological effect) with market approach hinges on the coefficient of purification (i.e., $N{P}_{t}$, $N{N}_{t}^{}$) under probability ${p}_{tp}$ (m
^{3}) in period t. $D{A}_{tm}^{N}$ and $D{A}_{tm}^{P}$ are the actual pollution purification capacities through ecological effect with a market approach (ton). $N{P}_{t}$ and $N{N}_{t}^{}$ are the coefficient of purification with consideration of ecological effect, which can be obtained based on previous research works. Models (2f) and (2g) present that pollutant discharges from crop irrigation would impose restrictions on discharge allowance (${TNP}_{tp}^{}$ and ${TPP}_{tp}^{}$). ${TNP}_{tp}^{}$ and ${TPP}_{tp}^{}$ are maximum allowable TN and TP discharges from irrigation in period t (ton), which have been expressed as credibility fuzzy manners. In fact, actual nitrogen and phosphorus discharges would be original discharge from irrigative activities minus the values that being purification through ecological effect [as shown in Models (2f) and (2g)]. Since the capacity of water conservation and soil erosion of forest can relieve the adverse effect from irrigation, Models (2h) and (2i) present that the total capacities of water and soil conservation would be restricted by their maximum capacities ($LW{T}_{tp}$ and $LS{T}_{tp}$) in study region. $LM{S}_{tm}$ and $LM{W}_{tn}$ are the coefficients of ecological effect for soil and water conservation from a forest system in period t (%). $LW{T}_{tp}$ and $LS{T}_{tp}$ are maximum allowances for water and soil erosion in period t (ton). - Non-negativity:$$W{M}_{tm}>S{M}_{tm}\ge 0,\text{\hspace{1em}\hspace{1em}}WE{A}_{tm}>SE{A}_{tm}\ge 0$$Model (2j) is non-negativity restrictions.

#### 2.4. Data Acquisition

## 3. Result Analysis

#### 3.1. Adverse Effects from Crop Irrigation without Market Approach

^{6}m

^{3}when water inflows are low, low-medium, medium, medium-high, and high levels, respectively, when η is 0.6. Meanwhile, the results display that deficits are influenced by various η-levels. The higher η-level (i.e., η = 0.99) would result in higher water deficits; by decreasing η-level, water deficits would drop (i.e., η = 0.6). For example, when water availability is low level in Period 3, water deficits of shelter forest would be 3.16 × 10

^{6}m

^{3}(η = 0.6) and 3.75 × 10

^{6}m

^{3}(η = 0.99). In comparison, the highest water deficit area would occur in grain plant due to its excessive planting scale. On the contrary, economic forest has a lowest water deficit, which indicates that expected land demand targets for economic forest would be rational in study region. Meanwhile, it implies that economic forest has a higher potential to be expanded due to its rational scale and higher ecological effect.

^{6}ton, respectively. (b) The results determine that the crop planation scale and corresponding pollutant discharge rate of varied crop planation can generate different amount of pollutant discharge. Meanwhile, various policy scenarios associated with changed allowable discharges can be considered. In the study region, based on calculation of environmental loads, policymakers have restricted maximum allowances (${TNP}_{tp}^{}$ and ${TPP}_{tp}^{}$) for TN and TP discharges. The results indicate that looser allowance would bring about a lower excess discharge, and vice versa.

#### 3.2. Land Trade between Forest and Irrigation

^{6}ha at maximum) due to its lower net economic benefit and higher emission compared to the other irrigated productions. (b) Forest can be considered a buyer to recover forest land to improve the system benefits from ecological effects. Among the three types of forest recovery methods, the economic forest has a better economic benefit and ecological return than shelter forest and ecological park. Under this situation, the highest recovered forest would be economic forest, which would reach 0.89 × 10

^{6}ha at maximum. (c) The trend of land transition indicates that the current oversized planting scale in grain plant based on food security policy would generate a higher risk of environmental pollution, which easily leads to system failure. (d) The results present that the water availability levels would influence the land transactions between irrigated production and forest recovery. For instance, in Case 1, the area of withdrawing cultivation in oil planting would be 0.46, 0.22 and 0 × 10

^{6}ha when water levels are low, medium and high in Period 2, respectively. It indicates that land resources and water resources, both deemed important impact factors, could be incorporated into an ICFM project to adjust current policy in study region.

#### 3.3. Ecological Effects and Corresponding Benefit from Market Approach

#### 3.4. System Benefit with and without Market Approach

^{9}to $1.24 × 10

^{9}, with increasing η-necessity levels from 0.60 to 0.995. It means that a lower η level and increased uncertainty for the imprecise objective would correspond to an optimistic attitude on the expected system benefit, and vice versa. Meanwhile, the market approach is a more effective method for land planning, which can generate a higher benefit than that with non-market approach. For example, when η is 0.9, system benefits would be $1.08 × 10

^{9}with market approach, while system benefits are $0.94 × 10

^{9}without market approach.

## 4. Conclusions

^{6}m

^{3}(α = 0.6, ε = 0.99), leading to a loss. It means that the accelerated irrigative expansion has exceeded what water resources can afford. Thus, the adjusting the rate of agricultural development is an important issue for regional policymaker. (b) The results display that existing land utilization would produce excessive pollution to increase ecological risk in study region, where the highest excessive TP and TN discharges would reach 432.24 and 14.32 × 10

^{3}ton. (c) The results indicate that strategies for ecological expansions (convert cultivated land into forest) can decrease the excessive pollutant discharges and water deficits, which can generate a higher system benefit than that without withdrawing farmland and recovering forest.

## Author Contributions

## Acknowledgments

## Conflicts of Interest

## Appendix A

## References and Notes

- Mensing, D.M.; Galatowitsch, S.M.; Tester, J.R. Anthropogenic effects on the biodiversity of riparian forests of a northern temperate landscape. J. Environ. Manag.
**1998**, 53, 349–377. [Google Scholar] [CrossRef] - Rai, R.; Zhang, Y.; Paudel, B.; Li, S.; Khanal, N.R. A synthesis of studies on land use and land cover dynamics during 1930–2015 in Bangladesh. Sustainability
**2017**, 9, 1866. [Google Scholar] [CrossRef] - Motesharrei, S.; Rivas, J.; Kalnay, E. Human and nature dynamics (HANDY): Modeling inequality and use of resources in the collapse or sustainability of societies. Ecol. Econ.
**2014**, 101, 90–102. [Google Scholar] [CrossRef] - Weißhuhn, P.; Reckling, M.; Stachow, U.; Wiggering, H. Supporting agricultural ecosystem services through the integration of perennial polycultures into crop rotations. Sustainability
**2017**, 9, 2267. [Google Scholar] [CrossRef] - Calatrava, J.; Garrido, A. Spot water markets and risk in water supply. Agric. Econ.
**2005**, 33, 131–143. [Google Scholar] [CrossRef] - Li, Y.P.; Huang, G.H.; Xiao, H.N.; Qin, X.S. An inexact two-stage quadratic program for water resources planning. J. Environ. Inform.
**2007**, 10, 99–105. [Google Scholar] - Abildtrup, J.; Garcia, S.; Stenger, A. The effect of forest land use on the cost of drinking water supply: A spatial econometric analysis. Ecol. Econ.
**2013**, 92, 126–136. [Google Scholar] [CrossRef] - Ondei, S.; Prior, L.D.; Williamson, G.J.; Vigilante, T.; Bowman, D.M. Water, land, fire, and forest: Multi-scale determinants of rainforests in the Australian monsoon tropics. Ecol. Evol.
**2017**, 7, 1592–1604. [Google Scholar] [CrossRef] [PubMed] - Samie, A.; Deng, X.; Jia, S.; Chen, D. Scenario-based simulation on dynamics of land-use-land-cover change in Punjab province, Pakistan. Sustainability
**2017**, 9, 1285. [Google Scholar] [CrossRef] - Johnson, K.A.; Polasky, S.; Nelson, E.; Pennington, D. Uncertainty in ecosystem services valuation and implications for assessing land use tradeoffs: An agricultural case study in the Minnesota River Basin. Ecol. Econ.
**2012**, 79, 71–79. [Google Scholar] [CrossRef] - Zeng, X.T.; Yang, X.L.; Yu, L.Y.; Chen, H.L. A mix inexact-quadratic fuzzy water resources management model of floodplain (IQT-WMMF) for regional sustainable development of Dahuangbaowa, China. Water
**2015**, 7, 2771–2795. [Google Scholar] [CrossRef] - Perez-Garcia, J.; Joyce, L.A.; Mcguire, A.D. Temporal uncertainties of integrated ecological/economic assessments at the global and regional scales. For. Ecol. Manag.
**2002**, 162, 105–115. [Google Scholar] [CrossRef] - Hauk, S.; Gandorfer, M.; Wittkopf, S.; Müller, U.K.; Knoke, T. Ecological diversification is risk reducing and economically profitable—The case of biomass production with short rotation woody crops in south German land-use portfolios. Biomass Bioenergy
**2017**, 98, 142–152. [Google Scholar] [CrossRef] - Zeng, X.T.; Li, Y.P.; Huang, W.; Bao, A.M.; Chen, X. Two-stage credibility-constrained programming with Hurwicz criterion (TCP-CH) for planning water resources management. Eng. Appl. Artif. Intell.
**2014**, 35, 164–175. [Google Scholar] [CrossRef] - Whelan, M.J.; Hope, E.G.; Fox, K. Stochastic modelling of phosphorus transfers from agricultural land to aquatic ecosystems. Water Sci. Technol.
**2002**, 45, 167–175. [Google Scholar] [PubMed] - Han, Y.; Huang, Y.; Wang, G. Interval-parameter linear optimization model with stochastic vertices for land and water resources allocation under dual uncertainty. Environ. Eng. Sci.
**2011**, 28, 197–205. [Google Scholar] [CrossRef] - Djanibekov, U.; Khamzina, A. Stochastic economic assessment of afforestation on marginal land in irrigated farming system. Environ. Resour. Econ.
**2016**, 63, 95–117. [Google Scholar] [CrossRef] - Djanibekov, U.; Villamor, G.B. Market-based instruments for risk-averse farmers: Rubber agroforest conservation in Jambi Province, Indonesia. Environ. Dev. Econ.
**2016**, 22, 133–155. [Google Scholar] [CrossRef] - Guo, P.; Huang, G.H.; Li, Y.P. Inexact Fuzzy-Stochastic Programming for Water Resources Management Under Multiple Uncertainties. Environ. Model. Assess.
**2010**, 15, 111–124. [Google Scholar] [CrossRef] - Zeng, X.T.; Zhao, J.Y.; Yang, X.L.; Wang, X.; Xu, C.W.; Cui, L.; Zhou, Y. A land-indicator-based optimization model with trading mechanism in wetland ecosystem under uncertainties. Ecol. Indic.
**2017**, 74, 279–299. [Google Scholar] [CrossRef] - Dunn, S.M.; Brown, I.; Sample, J.; Post, H. Relationships between climate, water resources, land use and diffuse pollution and the significance of uncertainty in climate change. J. Hydrol.
**2012**, 434–435, 19–35. [Google Scholar] [CrossRef] - Inuiguchi, M.; Ramík, J. Possibilistic linear programming: A brief review of fuzzy mathematical programming and a comparison with stochastic programming in portfolio selection problem. Fuzzy Sets Syst.
**2000**, 111, 3–28. [Google Scholar] [CrossRef] - Altunkaynak, A.; Sen, Z. Fuzzy logic model of lake water level fluctuations in Lake Van, Turkey. Theor. Appl. Climatol.
**2007**, 90, 227–233. [Google Scholar] [CrossRef] - Maqsood, I.; Huang, G.H.; Yeomans, J.S. An interval-parameter fuzzy two-stage stochastic program for water resources management under uncertainty. Eur. J. Oper. Res.
**2005**, 167, 208–225. [Google Scholar] [CrossRef] - Deng, X.; Xu, Y.; Han, L.; Yu, Z.; Yang, M. Assessment of river health based on an improved entropy-based fuzzy matter-element model in the Taihu Plain, China. Ecol. Indic.
**2015**, 57, 85–95. [Google Scholar] [CrossRef] - Chena, M.J.; Huang, G.H. A derivative algorithm for inexact quadratic program-application to environmental decision-making under uncertainty. Eur. J. Oper. Res.
**2001**, 128, 570–586. [Google Scholar] [CrossRef] - Huang, G.H.; Loucks, D.P. An inexact two-stage stochastic programming model for water resources management under uncertainty. Civ. Eng. Environ. Syst.
**2000**, 17, 95–118. [Google Scholar] [CrossRef] - Liu, B.; Liu, Y.K. Expected value of fuzzy variable and fuzzy expected value models. IEEE Trans. Fuzzy Syst.
**2002**, 10, 445–450. [Google Scholar] - Trumbo, C.W.; McComa, K.A. The Function of Credibility in Information Processing for Risk Perception. Risk Anal.
**2003**, 23, 343–353. [Google Scholar] [CrossRef] [PubMed] - The statistical yearbook of Henan province (SYH), 2000, China, 2001.
- The statistical yearbook of Henan province (SYH), 2004, China, 2005.
- The statistical yearbook of Henan province (SYH), 2009, China, 2010.
- The statistical yearbook of Henan province (SYH), 2013, China, 2014.

**Figure 2.**Framework of land utilization pattern with consideration of ecological effect under uncertainties.

**Figure 3.**Water deficits without market approach when μ are 0.6 and 0.99. (low water flow denoted as L, low-medium water flow denoted as LM, medium water flow denoted as M, medium water flow denoted as MH).

**Figure 4.**Excessive pollutant discharges without market approach when μ is 0.6. (total nitrogen denoted as TN, total phosphorus denoted as TP).

**Figure 5.**Land trades between forest and agriculture when μ is 0.6 (grain plant is denoted as CP, oil plants is denoted as OP, vegetable is denoted as VP, economic forest is denoted as EP, shelter forest is denoted as SP, and forest park is denoted as FP).

**Figure 7.**The amounts of land trading and corresponding ecological benefits when μ is 0.6 (note: pollutant purification is denoted as PP, soil conservation is denoted as SI and water conservation is denoted as WC).

Sector | Period | |||
---|---|---|---|---|

t = 1 | t = 2 | t = 3 | ||

Net Benefit ($10^{3}/ha) | ||||

Farming corps | Grain | (11.0 ✕ $W{M}_{tm}$ + 210.7) | (8.0 ✕ $W{M}_{tm}$ + 229.0) | (9.0 ✕ $W{M}_{tm}$ + 255.0) |

Oil plants | (23.0 ✕ $W{M}_{tm}$ + 203.3) | (5.0 ✕ $W{M}_{tm}$ + 257.0) | (7.0 ✕ $W{M}_{tm}$ + 260.7) | |

Vegetable | (9.0 ✕ $W{M}_{tm}$ + 225.0) | (8.0 ✕ $W{M}_{tm}$ + 237.0) | (9.0 ✕ $W{M}_{tm}$ + 265.0) | |

Forest system | Economic forest | (5.5 ✕ $WE{A}_{tn}$ + 181.6) | (11.5 ✕ $WE{A}_{tn}$ + 198.6) | (11.5 ✕ $WE{A}_{tn}$ + 254.7) |

Shelter forest | (75.5 ✕ $WE{A}_{tn}$ + 177.0) | (75.5 ✕ $WE{A}_{tn}$ + 202.0) | (85.5 ✕ $WE{A}_{tn}$ + 237.6) | |

Forest park | (75.5 ✕ $WE{A}_{tn}$ + 184.0) | (145.5 ✕ $WE{A}_{tn}$ + 188.6) | (85.5 ✕ $WE{A}_{tn}$ + 227.0) | |

Penalty of Water Deficit ($10^{3}/ha) | ||||

Farming corps | Grain | (6.5 ✕ $S{M}_{tm}$ + 316.67) | (8.0 ✕ $S{M}_{tm}$ + 329.0) | (9.0 ✕ $S{M}_{tm}$ + 355.0) |

Oil plants | (23.0 ✕ $S{M}_{tm}$ + 303.9) | (5.0 ✕ $S{M}_{tm}$ + 35.07) | (7.0 ✕ $S{M}_{tm}$ + 360.6) | |

Vegetable | (7.5 ✕ $S{M}_{tm}$ + 336.0) | (7.0 ✕ $S{M}_{tm}$ + 341.3) | (9.0 ✕ $S{M}_{tm}$ + 357.6) | |

Forest system | Economic forest | (5.5 ✕ $SE{A}_{tn}$ + 281.6) | (11.5 ✕ $SE{A}_{tn}$ + 298.7) | (11 ✕ $SE{A}_{tn}$ + 354.6) |

Shelter forest | (7.0 ✕ $SE{A}_{tn}$ + 277.0) | (7.0 ✕ $SE{A}_{tn}$ + 302.0) | (8.5 ✕ $SE{A}_{tn}$ + 337.8) | |

Forest park | (7.0 ✕ $SE{A}_{tn}$ + 284.0) | (14.0 ✕ $SE{A}_{tn}$ + 288.6) | (8.5 ✕ $SE{A}_{tn}$ + 327.0) |

Period | ||||
---|---|---|---|---|

t = 1 | t = 2 | t = 3 | ||

Maximum irrigation scale (ha) | Grain plant | 1635 | 1678 | 1724 |

Oil plant | 165 | 189 | 222 | |

Vegetable plant | 350 | 388 | 416 | |

TP discharge rate of crop irrigation (10^{−3} ton/ha year) | Grain plant | 9.8 | 9.9 | 10 |

Oil plant | 9.1 | 9.1 | 9.2 | |

Vegetable plant | 10.2 | 10.3 | 10.2 | |

TN discharge rate of crop irrigation (10^{−3} ton/ha year) | Grain plant | 0.43 | 0.45 | 0.46 |

Oil plant | 0.45 | 0.45 | 0.45 | |

Vegetable plant | 0.52 | 0.52 | 0.53 | |

Maximum allowance total TP discharge (10^{3} ton/year) | 2.35 | 2.43 | 2.56 | |

Maximum allowance total TN discharge (10^{3} ton/year) | 0.33 | 0.36 | 0.39 |

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Zeng, X.; Cui, L.; Tan, Q.; Li, Z.; Huang, G.
A Sustainable Land Utilization Pattern for Confirming Integrity of Economic and Ecological Objectives under Uncertainties. *Sustainability* **2018**, *10*, 1307.
https://doi.org/10.3390/su10051307

**AMA Style**

Zeng X, Cui L, Tan Q, Li Z, Huang G.
A Sustainable Land Utilization Pattern for Confirming Integrity of Economic and Ecological Objectives under Uncertainties. *Sustainability*. 2018; 10(5):1307.
https://doi.org/10.3390/su10051307

**Chicago/Turabian Style**

Zeng, Xueting, Liang Cui, Qian Tan, Zhong Li, and Guohe Huang.
2018. "A Sustainable Land Utilization Pattern for Confirming Integrity of Economic and Ecological Objectives under Uncertainties" *Sustainability* 10, no. 5: 1307.
https://doi.org/10.3390/su10051307