Salinity leaching is necessary to sustain agricultural production in irrigated croplands. Improving salinity leaching efficiency not only conserves water but also reduces groundwater contamination. Current leaching requirement (LR) calculations are based on steady-state and one-dimensional (1D) approaches, and consequently, this LR concept may not be applicable to drip irrigation (approximately 2D), which is becoming more common due to its higher water use efficiency. The aims of this study were to assess the salinity leaching fraction (LF) in clay, loam, and sand soils under 1D (to mimic sprinkler irrigation) and 2D (to mimic drip irrigation) transient conditions with a numerical model (HYDRUS). Water applications used the actual irrigation scheme in an almond orchard located in central California without considering precipitation. Model simulations showed that soil salinity at the lower boundary (depth of 150 cm) reached steady-state in 10 years in HYDRUS-1D simulations. The leaching fractions calculated from the ratio of drainage-water depth to irrigation-water depth (LF w = D dw /D iw ) and irrigation-water salinity to drainage-water salinity (LF EC = EC iw /EC dw ) from HYDRUS-1D were similar among different textured soils. However, they were much higher under drip irrigation (2D) than under sprinkler irrigation (1D) when the same amount of water was applied, and LF EC values were much greater than the LF w values under 2D simulations. Salt balance (SB) and leaching efficiency (LE) indicated that sprinkler irrigation (1D) is more effective for salinity leaching than drip irrigation (2D). To improve salinity leaching efficiency, further evaluation of LRs under drip irrigation is needed.

Honghu Lake, located in the southeast of Hubei Province, China, has suffered a severe disturbance during the past few decades. To restore the ecosystem, the Honghu Lake Wetland Protection and Restoration Demonstration Project (HLWPRDP) has been implemented since 2004. A back propagation (BP) artificial neural network (ANN) approach was applied to evaluatinig the ecosystem health of the Honghu Lake wetland. And the effectiveness of the HLWPRDP was also assessed by comparing the ecosystem health before and after the project. Particularly, 12 ecosystem health indices were used as evaluation parameters to establish a set of three-layer BP ANNs. The output is one layer of ecosystem health index. After training and testing the BP ANNs, an optimal model of BP ANNs was selected to assess the ecosystem health of the Honghu Lake wetland. The result indicates that four stages can be identified based on the change of the ecosystem health from 1990 to 2008 and the ecosystem health index ranges from morbidity before the implementation of HLWPRDP (in 2002) to middle health after the implementation of the HLWPRDP (in 2005). It demonstrates that the HLWPRDP is effective and the BP ANN could be used as a tool for the assessment of ecosystem health.

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