Identification of different pollution sources in groundwater is challenging, especially in areas with diverse land uses and receiving multiple inputs. In this study, principal component analysis (PCA) was combined with geographic information system (GIS) to explore the spatial and temporal variation of groundwater quality and to identify the sources of pollution and main factors governing the quality of groundwater in a multiple land-use area in southwestern China. Groundwater samples collected from 26 wells in 2012 and 38 wells in 2018 were analyzed for 13 water quality parameters. The PCA results showed that the hydro-geochemical process was the predominant factor determining groundwater quality, followed by agricultural activities, domestic sewage discharges, and industrial sewage discharges. Agriculture expansion from 2012 to 2018 resulted in increased apportionment of agricultural pollution. In contrast, economic restructure and infrastructure improvement reduced the contributions of domestic sewage and industrial pollution. Anthropogenic activities were found the major causes of elevated nitrogen concentrations (NO3−, NO2−, NH4+) in groundwater, highlighting the necessity of controlling N sources through effective fertilizer managements in agricultural areas and reducing sewage discharges in urban areas. The applications of GIS and PCA successfully identified the sources of pollutants and major factors driving the variations of groundwater quality in tested years.

Groundwater pollution source apportionment using principal component analysis in a multiple land-use area in southwestern China

Assessing the impact of water price reform on farmers’ willingness to pay for agricultural water in northwest China

Exploring parsimonious daily rainfall-runoff model structure using the hyperbolic tangent function and Tank model

Willingness to pay for irrigation water when groundwater is scarce

Understanding catchment response to rainfall events is important for accurate runoff estimation in many water-related applications, including water resources management. This study introduced a hybrid model, the Tank-least squared support vector machine (LSSVM), that incorporated intermediate state variables from a conceptual tank model within the least squared support vector machine (LSSVM) framework in order to describe aspects of the rainfall-runoff (RR) process. The efficacy of the Tank-LSSVM model was demonstrated with hydro-meteorological data measured in the Yongdam Catchment between 2007 and 2016, South Korea. We first explored the role of satellite soil moisture (SM) data (i.e., European Space Agency (ESA) CCI) in the rainfall-runoff modeling. The results indicated that the SM states inferred from the ESA CCISWI provided an effective means of describing the temporal dynamics of SM. Further, the Tank-LSSVM model’s ability to simulate daily runoff was assessed by using goodness of fit measures (i.e., root mean square error, Nash Sutcliffe coefficient (NSE), and coefficient of determination). The Tank-LSSVM models’ NSE were all classified as “very good” based on their performance during the training and testing periods. Compared to individual LSSVM and Tank models, improved daily runoff simulations were seen in the proposed Tank-LSSVM model. In particular, low flow simulations demonstrated the improvement of the Tank-LSSVM model compared to the conventional tank model.

https://www.mdpi.com/2072-4292/12/11/1801/pdf

A Hybrid Approach Combining Conceptual Hydrological Models, Support Vector Machines and Remote Sensing Data for Rainfall-Runoff Modeling

The long-term nitrogen pollution load potential (NPLPg) to groundwater from farmlands was examined in the Tedori River Basin. The NPLPg was estimated using the difference between N in the fertilizer application rate and N outputs in crop yield at 5-yearly intervals from 1960 to 2005. The total yearly NPLPg of 1,085 t (103 kg) in the 1960s decreased to 774 t by 1975. Thereafter, the NPLPg gradually increased to 976 t in the 1990s, but decreased again to 369 t in 2005. The NPLPg decreased by 23% for rice and by 37% for horticultural crops from 1960 to 2005 with an overall decrease of 34%. The NPLPg per unit area was relatively stable over time for rice, soybean, barley, and horticultural crops, but there were significant differences among them. The NPLPg for rice ranged from 39 to 85 kg ha−1 year−1 with an average of 65 kg ha−1 year−1 and that of the horticultural crops ranged from 273 to 357 kg ha−1 year−1 with an average of 302 kg ha−1 year−1 The significant long-term changes in the NPLPg suggest that evaluation at a specific point in time is insufficient for an integrated assessment of groundwater pollution.

Assessment of the long-term variation in the nitrogen pollution load potential from farmland to groundwater in the Tedori River Basin, Japan

In order to confirm that the regional function of Kanazawa’s irrigation water is representative of the urban type, and that Shichika’s irrigation water is representative of the rural, the contingent valuation method (CVM) was applied to determine the economic value of the functions aside from agricultural production, that is, the multi-functional roles of the irrigation water. The economic value of the regional function in Kanazawa was significantly lower than in the Shichika area, reflecting a difference in charge for irrigation water and people’s preference or consciousness in urban and rural areas. In urban areas, people tend to place a higher value on ground view, peace of mind and environmental friendliness. In contrast, in rural areas, irrigation water is presently used for domestic purposes. In other words, in urban areas people see water as public goods, while in rural areas the people see water as private goods. In addition, differences in the economic value of each item that was statistically significant for CVM were estimated using the Turnbull model comparing the items approved or rejected by the respondent.

An economic evaluation of Kanazawa and Shichika irrigation water’s multi-functional roles using CVM

An Evaluation of Snow Storage Depth in the Tedori River Basin Using Tank Model

We investigate the effect of climate change on water resources as snow storage (WRSS) using a regional climate model with a 20-km mesh (MRI-RCM20), in the Tedori River basin of Japan. We make four main predictions. First, annual average temperature in Kanazawa is predicted to increase by 2.7 °C by 2081–2100, compared to the period 1981–2000. The smallest predicted temperature difference is 1.1 °C in August, and the largest is 3.4 °C in April and December. The annual average temperature is predicted to change from 14.5 to 17.2 °C. Second, annual average precipitation is predicted to increase by 3.8 %, and precipitation during the snowfall season (December–February) is predicted to decrease by 13.2 %, as a result of increasing temperatures. Third, average WRSS for the period 2001–2100 is predicted by degree-day and tank model analyses. Both the analyses show very similar results. The degree-day analysis shows 200 mm of average WRSS in 2100, and 477 mm in 2050. These values constitute 26 and 63 % of the WRSS value in 2000 (754 mm). The tank model analysis shows WRSS of 260 mm in 2100 and 523 mm in 2050, which are 33 and 67 % of the WRSS (785 mm) in 2000, respectively. Fourth, to examine the effect on irrigation water especially on the paddy paddling period, discharge is predicted and considered under the predicted average WRSS is 520 mm in 2050, 258 mm in 2100, and reaches a minimum of 41 mm in 2100.

Prediction of water resources as snow storage under climate change in the Tedori River basin of Japan

Return flow and repeated use of irrigation water for paddies is the most important issue in the Asian monsoon region, because sometimes this water is applied in greater quantity than that of evapotranspiration plus percolation. A new return flow analysis, the “replacement-in-order method”, which introduces a unique numbering system for very complicated irrigation and drainage networks, is proposed for the main canal with the dual purposes of irrigation and drainage. The method is applied to the Shichika irrigation district in the ordinal (season) irrigation period, resulting in a return flow ratio of 45 % for the entire area. Of this amount, 25 % is available for irrigation again. The remaining 20 % is unavailable, because the return flow discharged directly into a canal lacking a diversion weir in the drainage system, or into the Japan Sea. The return flow ratio is very different at the main canal location, from no return flow to 88 %. With the aid of the above method, theoretical analysis of return flow for paddy irrigation water can be done. This includes the deterministic return flow ratio inside and outside the irrigation area, plus precise information of return flow ratios at various main canal locations and routes of irrigation and drainage water.

Proposal of new return flow analysis by replacement-in-order method for paddy irrigation water

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