论系统论视域下的流域生态环境行政治理

流域及其生态环境问题的特殊性引发行政治理体系的变革,系统论为流域生态环境行政治理体系的建构指明了方向,流域生态环境行政治理体系的建构是系统化的工程。在系统论指引下,结合相关规范性文件,流域生态环境行政治理系统的建构需从建立协调机制、规范职权行使与推进治理协同三方面切入,并分别明确三者在流域生态环境行政治理系统中的作用,通过建立议事协调机构发挥协调机制的统筹协调功能、通过整合与上收行政机关职权明确规范职权行使的实施功能、通过建立治理协同机制发挥推进治理协同的支持与保障功能。     

PRISM vs. CFSR Precipitation Data Effects on Calibration and Validation of SWAT Models

Precipitation is one of the most important drivers in watershed models. Our objective was to compare two sources of interpolated precipitation data in terms of their effect on calibration and validation of two Soil and Water Assessment Tool (SWAT) models. One model was a suburban watershed in metropolitan Atlanta, Georgia. The precipitation sources were Parameter‐elevation Relationships on Independent Slopes Model (PRISM) data on a 4‐km grid and climate forecast system reanalysis (CFSR) data on a 38‐km grid. The PRISM data resulted in a better fit to the calibration data (Nash Sutcliffe efficiency [NSE] = 0.64, Kling‐Gupta efficiency [KGE] = 0.74, p‐factor = 0.84, and r‐factor = 0.43) than the CFSR data (NSE = 0.47, KGE = 0.53, p‐factor = 0.67, and r‐factor = 0.39). Validation results were similar. Sensitive parameters were similar in both the PRISM and CFSR models, but fitted values indicated more rapid groundwater flow to the streams with the PRISM data. The same comparison was made in the Big Creek watershed located approximately 1,000 km away, in central Louisiana. Results were similar with a more responsive groundwater system indicating PRISM data may produce better predictions of streamflow because of a more accurate estimate of rainfall within a watershed or because of a denser grid. Our study implies PRISM is providing a better estimate than CFSR of precipitation within a watershed when rain gauge data are not available, resulting in more accurate simulations of streamflows at the watershed outlet. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Estimation of Catchment Nutrient Loads in New Zealand Using Monthly Water Quality Monitoring Data

Causes of variation between loads estimated using alternative calculation methods and their repeatability were investigated using 20 years of daily flow and monthly concentration samples for 77 rivers in New Zealand. Loads of dissolved and total nitrogen and phosphorus were calculated using the Ratio, L5, and L7 methods. Estimates of loads and their precision associated with short‐term records of 5, 10, and 15 years were simulated by subsampling. The representativeness of the short‐term loads was quantified as the standard deviation of the 20 realizations. The L7 method generally produced more realistic loads with the highest precision and representativeness. Differences between load estimates were shown to be associated with poor agreement between the data and the underlying model. The best method was shown to depend on the match between the model and functional and distributional characteristics of the data, rather than on the contaminant. Short‐term load estimates poorly represented the long‐term load estimate, and deviations frequently exceeded estimated imprecision. The results highlight there is no single preferred load calculation method, the inadvisability of “unsupervised” load estimation and the importance of inspecting concentration‐flow, unit load‐flow plots and regression residuals. Regulatory authorities should be aware that the precision of loads estimated from monthly data are likely to be “optimistic” with respect to the actual repeatability of load estimates.     

The Watershed Flow and Allocation Model: An NHDPlus‐Based Watershed Modeling Approach for Multiple Scales and Conditions

The Watershed Flow and Allocation model (WaterFALL^®) provides segment‐specific, daily streamflow at both gaged and ungaged locations to generate the hydrologic foundation for a variety of water resources management applications. The model is designed to apply across the spatially explicit and enhanced National Hydrography Dataset (NHDPlus) stream and catchment network. To facilitate modeling at the NHDPlus catchment scale, we use an intermediate‐level rainfall‐runoff model rather than a complex process‐based model. The hydrologic model within WaterFALL simulates rainfall‐runoff processes for each catchment within a watershed and routes streamflow between catchments, while accounting for withdrawals, discharges, and onstream reservoirs within the network. The model is therefore distributed among each NHDPlus catchment within the larger selected watershed. Input parameters including climate, land use, soils, and water withdrawals and discharges are georeferenced to each catchment. The WaterFALL system includes a centralized database and server‐based environment for storing all model code, input parameters, and results in a single instance for all simulations allowing for rapid comparison between multiple scenarios. We demonstrate and validate WaterFALL within North Carolina at a variety of scales using observed streamflows to inform quantitative and qualitative measures, including hydrologic flow metrics relevant to the study of ecological flow management decisions.     

Modeling Summer Month Hydrological Drought Probabilities in the United States Using Antecedent Flow Conditions

Climate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States (U.S.) using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gages from January 1, 1884 through January 9, 2014 provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February, estimating outcomes 5‐11 months ahead of their occurrence. Few drought prediction methods exploit temporal links among streamflows. We find MLLR modeling of drought streamflow probabilities exploits the explanatory power of temporally linked water flows. MLLR models with strong correct classification rates were produced for streams throughout the U.S. One ad hoc test of correct prediction rates of September 2013 hydrological droughts exceeded 90% correct classification. Some of the best‐performing models coincide with areas of high concern including the West, the Midwest, Texas, the Southeast, and the Mid‐Atlantic. Using hydrological drought MLLR probability estimates in a water management context can inform understanding of drought streamflow conditions, provide warning of future drought conditions, and aid water management decision making.     

Data Management Dimensions of Social Water Science: The iUTAH Experience

Integrating social and hydrologic sciences for understanding water systems is challenged by data management complexities. Contemporary mandates for open science and data sharing necessitate better understanding of the implications of social science data types. In the context of an interdisciplinary water research program that endeavors to integrate and share social science and biophysical data, we highlight the array of data types and issues associated with social water science. We present a multi‐dimensional classification of social water science data that provides insight into data management considerations for each data type. Recommendations for cyberinfrastructure, planning, and policy are offered.     

协同引擎、外部环境与流域生态补偿多主体协同行为研究——以山东省大汶河流域为例

联合多方利益相关主体实施协同行为,提升多元异质性主体之间的协同性,对优化流域生态补偿机制效能至关重要。本文基于山东省大汶河流域的979份实地调研数据,运用层次回归与有调节的中介效应检验方法,实证剖析协同引擎、外部环境对流域生态补偿多主体协同行为的驱动机理。研究表明：①协同引擎对流域生态补偿多主体协同行为具有显著正向驱动作用;②协同意愿在协同引擎与协同行为之间起中介作用,协同引擎可通过强化协同意愿间接驱动协同行为;③外部环境正向调节协同意愿向协同行为的转化,政府规制与社会规范的调节作用均通过显著性检验;④有调节的中介效应检验结果显示,高水平的政府规制及社会规范影响下,协同意愿在协同引擎与协同行为之间的中介作用得到增强,但在低水平的政府规制与社会规范影响下,协同意愿的中介作用并不显著。     

Land-cover changes in an urban lake watershed in a mega-city, Central China

Urbanization can exert a profound influence on land covers and landscape characteristics. In this study, we characterize the impact of urbanization on land cover and lacustrine landscape and their consequences in a large urban lake watershed, Donghu Lake watershed (the largest urban lake in China), Central China, by using Landsat TM satellite images of three periods of 1987, 1993 and 1999 and ground-based information. We grouped the land covers into six categories: water body, vegetable land, forested land, shrub-grass land, open area and urban land, and calculated patch-related landscape indices to analyze the effects of urbanization on landscape features. We overlaid the land cover maps of the three periods to track the land cover change processes. The results indicated that urban land continuously expanded from 9.1% of the total watershed area in 1987, to 19.4% in 1993, and to 29.6% in 1999. The vegetable land increased from 7.0% in 1987, 11.9% in 1993, to 13.9% in 1999 to sustain the demands of vegetable for increased urban population. Concurrently, continuous reduction of other land cover types occurred between 1987 and 1999: water body decreased from 30.4% to 23.8%, and forested land from 33.6% to 24.3%. We found that the expansion of urban land has at least in part caused a decrease in relatively wild habitats, such as urban forest and lake water area. These alterations had resulted in significant negative environmental consequences, including decline of lakes, deterioration of water and air quality, and loss of biodiversity.     

Using SWAT to Model Streamflow in Two River Basins With Ground and Satellite Precipitation Data1

Abstract: Both ground rain gauge and remotely sensed precipitation (Next Generation Weather Radar – NEXRAD Stage III) data have been used to support spatially distributed hydrological modeling. This study is unique in that it utilizes and compares the performance of National Weather Service (NWS) rain gauge, NEXRAD Stage III, and Tropical Rainfall Measurement Mission (TRMM) 3B42 (Version 6) data for the hydrological modeling of the Middle Nueces River Watershed in South Texas and Middle Rio Grande Watershed in South Texas and northern Mexico. The hydrologic model chosen for this study is the Soil and Water Assessment Tool (SWAT), which is a comprehensive, physical‐based tool that models watershed hydrology and water quality within stream reaches. Minor adjustments to selected model parameters were applied to make parameter values more realistic based on results from previous studies. In both watersheds, NEXRAD Stage III data yields results with low mass balance error between simulated and actual streamflow (±13%) and high monthly Nash‐Sutcliffe efficiency coefficients (NS > 0.60) for both calibration (July 1, 2003 to December 31, 2006) and validation (2007) periods. In the Middle Rio Grande Watershed NEXRAD Stage III data also yield robust daily results (time averaged over a three‐day period) with NS values of (0.60‐0.88). TRMM 3B42 data generate simulations for the Middle Rio Grande Watershed of variable qualtiy (MBE = +13 to ?16%; NS = 0.38‐0.94; RMSE = 0.07‐0.65), but greatly overestimates streamflow during the calibration period in the Middle Nueces Watershed. During the calibration period use of NWS rain gauge data does not generate acceptable simulations in both watersheds. Significantly, our study is the first to successfully demonstrate the utility of satellite‐estimated precipitation (TRMM 3B42) in supporting hydrologic modeling with SWAT; thereby, potentially extending the realm (between 50°N and 50°S) where remotely sensed precipitation data can support hydrologic modeling outside of regions that have modern, ground‐based radar networks (i.e., much of the third world).     

Development of a SWAT Patch for Better Estimation of Sediment Yield in Steep Sloping Watersheds1

Abstract: The watershed scale Soil and Water Assessment Tool (SWAT) model divides watersheds into smaller subwatersheds for simulation of rainfall‐runoff and sediment loading at the field level and routing through stream networks. Typically, the SWAT model first needs to be calibrated and validated for accurate estimation through adjustment of sensitive input parameters (i.e., Curve Number values, USLE P, slope and slope‐length, and so on). However, in some instances, SWAT‐simulated results are greatly affected by the watershed delineation and Digital Elevation Models (DEM) cell size. In this study, the SWAT ArcView GIS Patch II was developed for steep sloping watersheds, and its performance was evaluated for various threshold values and DEM cell size scenarios when delineating subwatersheds using the SWAT model. The SWAT ArcView GIS Patch II was developed using the ArcView GIS Avenue program and Spatial Analyst libraries. The SWAT ArcView GIS Patch II improves upon the SWAT ArcView GIS Patch I because it reflects the topographic factor in calculating the field slope‐length of Hydrologic Response Units in the SWAT model. The simulated sediment value for 321 subwatersheds (watershed delineation threshold value of 25 ha) is greater than that for 43 subwatersheds (watershed delineation threshold value of 200 ha) by 201% without applying the SWAT ArcView GIS Patch II. However, when the SWAT ArcView GIS Patch II was applied, the difference in simulated sediment yield decreases for the same scenario (i.e., difference in simulated sediment with 321 subwatersheds and 43 subwatersheds) was 12%. The simulated sediment value for DEM cell size of 50 m is greater than that for DEM cell size of 10 m by 19.8% without the SWAT ArcView GIS Patch II. However, the difference becomes smaller (3.4% difference) between 50 and 10 m with the SWAT ArcView GIS Patch II for the DEM scenarios. As shown in this study, the SWAT ArcView GIS Patch II can reduce differences in simulated sediment values for various watershed delineation and DEM cell size scenarios. Without the SWAT ArcView GIS Patch II, variations in the SWAT‐simulated results using various watershed delineation and DEM cell size scenarios could be greater than those from input parameter calibration. Thus, the results obtained in this study show that the SWAT ArcView GIS Patch II should be used when simulating hydrology and sediment yield for steep sloping watersheds (especially if average slope of the subwatershed is >25%) for more accurate simulation of hydrology and sediment using the SWAT model. The SWAT ArcView GIS Patch II is available at http://www.EnvSys.co.kr/~swat for free download.